Professionals love the simplicity of SOSTAC® Planning method. This short book helps you to write plans that:

1. Get Approved
2. Boost Results
3. Make Better Decisions
4. Build Strong Strategies (separate from tactics)
5. Deliver a Reassuring Sense of Order

SOSTAC® has changed the work lives of so many marketers and business owners over the years.

SOSTAC® Delivers Success
whether growing businesses, winning pitches, attracting investors or getting a new job, SOSTAC® planning skills delivers great plans. SOSTAC® was voted in the Top 3 Biz Models Worldwide by the Chartered Inst of Marketing.

What They Say about SOSTAC®
‘saves time’
‘catapulted my career’
‘avoids costly omissions’
‘trebled our conversion rates’
‘creates impressive strategies’
‘a whole new world of logical thinking’
‘the clearest approach to strategic marketing planning’

See the full reviews on ‘Why Sostac?’  on the sostac.org  site

So, What’s New in SOSTAC® Guide 2025 (AI Ed)?

In addition to showing you how to:
ask great questions,
make better decisions and
write the perfect plan,

this 10^th edition, is very special.  

SOSTAC® Plans Explained

This SOSTAC® 2025 AI Edition also includes:

• The Advantages and Disadvantages of AI (1st chapter)
• 3 AI Waves + 4 AI Limiting Factors (1st chapter)
• The Essence of Ethics being central in AI 1st chapter)
• How AI’s Virtuous Data Cycle is also key (1st chapter)
• Some AI tools, tips and warnings – sprinkled throughout the book

Easy To Digest:
SOSTAC® can be learned in 3 minutes.
The 2025 Guide can be skimmed in 30 minutes
and digested fully in a few hours, prepping you to write great plans and/or to become a SOSTAC® Certified Planner.

I’ve tried to make this edition particularly entertaining as well as educating i.e. an edutainment experience.

If absorbed, this book will improve people’s work-lives, careers and organisations performances/results.

I really do hope you enjoy this SOSTAC® Guide 2025 (AI ed.). I welcome any feedback.

Paul
PR Smith

The SOSTAC® Guide to your Perfect Digital Marketing Plan 2025 (AI edition) is at last, finished, published and now, finally, available from Amazon.

We will talk about the SOSTAC 2025 AI ed. in our weekly chat about AI, Innovation & Ethics  on Friday at 1pm UK time (NB these 30 minute chats are now recorded. Go to my Linkedin and scroll down to ‘Events’ to listen live or previous chats.

The post What’s So Great About SOSTAC® & the SOSTAC® Guide 2025 AI edition? appeared first on PR Smith Marketing.

Enjoy this best-selling updated 8^th edition – packed with new material, keeping abreast with AI, AR, VR, MR, MA and other innovative approaches to marketing communications. All integrated with the world’s most popular SOSTAC® Planning methodology that delivers a reassuring sense of order in a chaotic digital world and also that delivers success from better, MarComms’ ‘information-based’ decisions.

In Part 2 – all ten marcomms tactical tools (incl ads, PR, sponsorship, Owned, Earned and Paid Media etc.)  has a sample SOSTAC® Plan at the end of chapter.

Ze Zook and I are so pleased with it.  So much new material including AI integrating with MarComms.  We’ve tried to keep the edutainment angle so readers actually enjoy discovering some cutting-edge examples, tips and tools throughout the book. Thanks to the team at @Kogan Page including: Alison, Donna, Bruna and  Jack, Jeylan, Susie and of course, Helen Kogan.

What New Marketing and What Classic Marketing is in the 8th ed.?

What’s new and what’s old in Marketing Communications 8th ed.?

20% author’s discount can be used legitimately by following these instructions.

1. Go to koganpage.com/MC8
2. Click ‘Add to Cart’
3. Click ‘Checkout’ on the top right corner of the screen.
4. Complete your Billing & Delivery Information
5. Click ‘Continue to Review & Pay’
6. Scroll down to ‘Review Items’
7. In this section, click the ‘Add an offer code’ button – bottom right
8. Enter your code AMK20 in the box provided
9. Scroll down to input your payment information
10. Click the ‘Buy Now’ button at the bottom of the screen.

Enjoy Your Book

The post Marketing Communications 8th ed Released! appeared first on PR Smith Marketing.

—

Chatbots can create competitive advantage. Ignore them at your peril. Here, we apply a #SOSTAC ®  Plan for developing your own chatbot.  Written by PR Smith and Tom Sickert.

Image by Parker_West from Pixabay

SOSTAC ® Planning Framework www.sostac.org

SITUATION ANALYSIS

Hyper-competition is here to stay and chatbots have a role to play. Data, AI, and chatbots in particular can create a new competitive advantage. Ignore these at your peril.

AI-driven chatbots can boost the CX (customer experience), strengthen existing customer relationships, reach new prospects, screen enquiries, identify best prospects, give them personalised answers/services instantaneously, convert to sales and thereafter be used to nurture stronger (potentially , lifetime, relationships).  Ignore chatbots at your peril.

Typical customer service staff feedback reveals: “We have all this excellent information on our public website – product description, prices, delivery times & costs, return policies… but still we get countless calls and emails about these.” It appears that many people are just not willing to work their way through websites, searching, scrolling and hoping to find a solution.

Should you have a Bot?

All customers have a ‘job to be done’ (Christensen et al 2016) when they visit a website (or an app). They want to find product information, check a price, read reviews, buy a product, be entertained, informed etc. Customers just want, access to the information or experience as quickly as possible (with or without a bot).

Chatbots or Humans – survey: what do people want?

Would anyone prefer to queue in a bank to withdraw money from a human or queue for an faceless automated cash withdrawal machine in the wall?

Bots present an opportunity to improve the relationship with both existing and potential new customers. This strengthens, what are arguably, your two greatest assets today: your brand, and your customer data in a new AI-supported world of chatbots. Let us apply this to a fictitious washing machine company.

OBJECTIVES

Be clear about why you want a chatbot? ‘Because everyone else has one’ is not a good enough answer. ‘Reduce costs’ is a popular answer but misses the real opportunity. The ultimate answer is to help customers to have a better CX (customer experience) and also identify your best potential lifetime customers. An AI-driven chatbot can instantaneously answer product questions, share advice, book appointments (for salespeople or technicians), take orders, trigger a follow-up onboarding series of messages in a personalised way 24/7/365.

All of these can, and should, be quantified objectives – in fact, SMART Objectives e.g. Boost CX Satisfaction Scores from 50% to 70 to 90% in years 1, 2 & 3 (or in Q1, Q2 and Q3?); Boost Net Promoter Scores (likelihood to recommend your service to a friend from 10 to 30 to 50); Reduce time taken for the visitor to purchase (reducing these times makes customers happy).

Cost-saving operational objectives are popular e.g. To reduce the number of calls/emails handled by 25% in the first 12 months.

More specific MVP (Minimum Viable Product) objectives can also be set. e.g.  the chatbot must help customers to:

• Find serial numbers and product names for all units produced by the company;
• Solving the top ten common problems – using images, links or text based on customer input;
• Create a service ticket for ALL ENQUIRIES (which includes capturing the customer phone number) so the helpdesk can call and resolve the customer’s issue via phone.

Be very clear about why you want an AI-Driven ChatBot. Think about how chatbots might help your business even more in, say, 3 years from now?    

Is ignoring chatbot potential to save money (and boost CX) like either  burying your head in the ground

Burying your head in the ground doesn’t solve any problems nor exploit any opportunities

or like throwing money down the toilet as you pay for slower, less personalised, human customer service?

Wasting Money

STRATEGY

Stage 1: Build a pilot AI ChatBot for Brand X washing machine website  –  aimed at helping customers find what washing machine is best for them, in a personalised, friendly and reassuring way. The chatbot dialogue must be knowledgeable yet friendly (to match the brand personality). Helping the customer in an informal way, yet demonstrating common sense knowledge (without jargon).

The chatbot must at all times support the values and the purpose of the overall business.   Environmentalism is an important issue for our customers, so and useful green guidance and tips should be offered where relevant and whenever the customer expresses interest (or wherever interest is detected e.g. if a visitor watches any of our green content e.g. ‘3 Tops Tips to Save Energy‘ video).

Data collection is critical to the long-term success of the AI-Supported chatbot and the business overall. Customer preferences, interests, demographics and other data feed into each customer profile, which in turn helps to find correlations to further improve both specially tailored offers and new products in the future.

Stage 2: Roll out to all other white good product range (e.g. washing machines,  dishwashers and microwaves) within 18 months and increasing NPS scores from 30 to 50 (as listed in the objectives).

Strategy

TACTICS

There are several tactical choices available when developing a chatbot .

1. Out-Of-The-Box Solutions, provided by vendors that have predefined models and features and functionalities, that can be customized based on your requirements. These solutions as well are powered (depending on your budget) by high performance AI solutions and features and functionalities. The provider of the chatbot solution can help you to assess your needs and find the optimal solution. There are now many chatbot companies including: Ada, AWS, Botsify, Chatfuel, Hubspot, Liveperson, Mobile Monkey, Microsoft’s Bot Framework and Cognitive Services

2. In-house Solution Created by ‘Citizen Developers’. These require NO code or LOW code experience and can be created by anybody who is able to create email rules in Microsoft Outlook. Yes, it is (mostly) that simple – these drag & drop (communication flow) solutions are offered by Microsoft and AMAZON alike. It gives you not too many options to customize and apply specific functionalities, but it sure is enough to for professional use. NB Citizen Development – no technical and programming skills needed.

3. Developed From Scratch – by coders and other IT professionals, in collaboration with your subject matter experts. These chatbots are powered either by custom AI with sophisticated algorithms and enhanced features and functionalities.

Sometimes out-of-the-box AI models are used as the basic framework e.g. Amazon’s LEX and Microsoft’s  Bot Framework and Cognitive Services solutions (object and image recognition, speech and sound recognition and reasoning). These can be tweaked later (either the interface or the code itself).

ACTIONS

In the end, the chatbot is just a little icon on your website.  However, there is still much work to be done. Miss these detailed ‘Actions’ and the AI Chatbot project will fail. Depending on which option you take will determine the details of the actions required.  Remember a chat project is never really finished. It can and should be continually improving via small tweaks and/or more data helping the chatbot to become more user helpful. So now the detailed work (actions) – we create the topics/answer, the question and 5-10 iterations of each question that can trigger the relevant answer.

Conversation Flows (marketing language)  / Decision Trees   

This In-house solution was created by ‘Citizen Developers’ (Tactical Option no.2).

Decision trees- conversation flows – from Microsoft Virtual Agents

You do not need any programme/development skills.   Conditions = scenarios – in this case, a condition can be whether you have a front loader washing machine or a top loader washing machine (see below).

Sample questions:

• When is the special sales weekend for your washing machines?
• When does my warranty expire?
• My washing machine is leaking, what should I do
• My washing turned pink, what can I do?
• I washed all my knives and forks in my washing machine by mistake – what should I do?

A script to help chatbot converse with a human customer/visitor

Optimised Resource Planning (also called RSO Resource Scheduling Optimization) is where AI can help customers to book the most appropriate technician (based on the particular problem description plus the items the customer has already checked) plus the customer’s and technician’s time and availability. The booking data is obviously also made accessible for the engineer.

Meanwhile, last but not least, is deployment. You have the chatbot developed and ready to go but how do you deploy it can determine its ultimate success or failure.  The key missing piece in the actions section of many plans is ‘internal marketing’ which comprise: communication, motivation and training.

Make sure people know about the chatbot development early on. Bring them with you. Communicate to them and motivate them about how this will help the business to survive in a hyper-competitive world. Remove fears of redundancy because of chatbots. Get people behind the idea. Perhaps consider redeploying staff into new jobs if the chatbot proves to be very successful – many of which will require training. Managing the chatbots may well require training and certainly going forward maintenance, coding, data analytics and reporting are just some of the jobs required.

NB It is critical that one person takes ownership of the chatbot from the very start, which leads us nicely into the final stage of SOSTAC(r) PLanning – Control – ‘how do we know we are getting there?’.

CONTROL

How do you measure success? Measure the KPIs you wrote in the Objectives section. NPS scores etc.

During the chatbot development stages, measure the MVP you have set . Then when you start testing/training the chatbot – watch closely, make fast changes and repeat.

Stay very close.  Watch your KPI Objectives. After that, you can start comparing last month’s KPIs to next month’s projections.  Don’t overcomplicate things.

Check the data you are collecting. Can it be used to give you insights on customer needs, what they like/don’t like?  What they need more help with? What helps you to identify your ideal customers? You will get a lot of data and insights that will allow you to dig deeper and drive     continual improvements.

Agree Your MVP (Minimum Viable Product) –  your version 1.0   and check to see if its working

e.g. “Tom and Paul agree that their MVP V1 must have following features & functionalities before deployment:

1. Include all washing machine types of their company with pictures and serial numbers so customers can easily identify their product
2. Know the top 10 problems customers can fix themselves and so that the chatbot can provide solutions via images, links or text based on customer input
3. Must have the function to immediately create a service ticket for the helpdesk to directly call the customer via phone
4. Must be able to converse in English and German for the aforementioned 3 features since UK and Germany are they key markets and pilot regions

Stay calm. Chatbots are complex.

In the end, it’s like driving a car – you are probably not an engineer – you simply use the technology. If things need to be fixed or improved – you go to the people whose job it is to do just that.

Supervising Your Chatbot’s Learning

An AI powered chatbot needs to be supervised to ensure that it LEARNS properly. In other words – you must TEACH it, give it supporting guidance and directions. That is achieved with defining “confidence scores” for each intent and related answers or information sources. Example:

• Customer asks: “How is the weather outside?”
  • The bot’s NLU and NLP identify “weather” and “outside” – giving a 99% confidence score that you are asking about the weather.
• Customer asks: “Is it sunny or rainy?”
  • The bot, in the beginning, will not be able to associate “sunny” and “rainy” with a question about the weather. So, it will give a very low confidence score. It might even respond with a wrong answer.

Managing Confidence Scores

Here is where managing confidence scores allow you to manage the responses. You screen the questions asked – filter, based on the automated confidence score the bot gave and begin to fine-tune and manually train your bot. That will take more time in the beginning – but with increased usage – it will take less time and provide better results.

Based on NLU (Natural Language Understanding) and NLP (Processing), the user’s intent is determined and, based on a confidence score – the answer selected is the one that is most feasible. Defining confidence levels is a balancing act   between say “I don’t know” vs giving the wrong answer.

This depends on how important a topic is from the customer’s perspective. And that goes already quite far into AI, machine learning and a bit into deep learning.  You ask:

• “What is the temperature tomorrow in Dublin” an 80% confidence score for the AI thinking you mean “what is the weather tomorrow in Dublin” is OK.
• “How long are the shops open today” a 99% confidence score for the AI would be needed to know that you mean “How long is the mall around the corner open today”?

Here are some examples for confidence scores and features you can apply:

If a question is asked and the bot does not fully understand (e.g. confidence score between 60% and 80%) – the bot could clarify it by suggesting topics e.g. “Did you ask about <topic x>”).

If the initial question has a confidence score between 75-90%, but the question has a typo – the chatbot will specifically reply: “You typed Dutsche Bnudselagi – did you mean Deutsche Bundesliga or Deutsche Bundesbank or Deutsche Bundespost?”.  Each option then could be directly selectable.

If the confidence score is below 50% (or any threshold you define), you can have the bot offering to connect directly to a person for a live-chat or simply respond “I am sorry, I do not understand what you ask. I know about <topic 1>, <topic 2>,…<topic x>. A properly phrased question could be this: “What is the cost for a top loader washing machine with energy level B?>”

Confidence scores should be reviewed and evaluated topic by topic and adjusted as needed to avoid giving out false information.

The Route to Success
is to define and create proper topics and help the AI to identify the intent based on keywords. If a question causes a confidence score lower than 50% the bot will basically say “I don’t understand” and send a message to the human team to check (and categorise) the question. Based on our review we then can create a completely new topic, adjust the confidence score to relate to an applicable answer, or connect with our developers in case there was actually a technical issue preventing the bot from answering.

Feed the AI with Questions and Answers
If we had 10 basic questions. And say, possibly 5 variations of each question. This is a very crude example of data set. This could be presented as a 3 column table or an excel sheet (see below).

Creat Variations (or ‘iterations’) of a basic question

Doing this manually is a citizen development approach but other approaches will often have some manual approaches too.

We attach an answer for each FAQ.   Each question and its variety of similar questions (‘iterations’ which basically ask the same question) will have an answer Linkedin to it. You can write all imaginable iterations of a question and then link it to the same answer.

Say you have 5 versions (iterations) of a question the chatbot identifies the INTENT (from the use of the keywords in the question) and then provides the answer.

Answers as well can be in various types and formats e.g. pictures and/or videos or text attached to an answer? E.g. take the live weather feed from youtube.

RESOURCES (the 4Ms)

What Resources Do You Need (The 4 Ms)?

Men and Women (human resource) + money (budgets)  + minutes (timescales) +megadata (data – structured and unstructured). ‘Resources Required’ depend on the company’s maturity and readiness in various areas.

MEN AND WOMEN  A different company that created an internal chatbot had the following resources: a strategic leader, 3 subject matter experts from the team, 4 external developers and 4 Microsoft specialists who’s support was included in the contract with Microsoft. They needed 9 months from version 0.0 to deploy version 1.0.

MONEY  (budget) A project manager can allocate a number of hours each week to the project. This can be fully costed. Then there are also license costs which vary enormously e.g. from $400 pm to $4,000 pm for, say, 10,000 requests p.m. Alternatively, a Flat Fee can be fixed at whether you have 1 enquiry or 1m enquiries.  Ask the question: ‘If I get x000,000 viewers/enquiries how much will it cost?’

Hosting – you need to check if the above costs include the cost to host the application (the bot itself) on (a) CSP (Cloud Service Provider) like Microsoft, Google, IBM, AWS plus give the bot access to your data or (b) on-premises (data centre). You can easily spend hundreds of thousands on a solution that makes AMAZON jealous with dozens of developers and features and functionalities and with connections to data sources. Here is where a Solution Architect, Solution Designer or a representative from a vendor can help to calculate and estimate costs and feasibility.

MEGA-DATA Data includes all data – both structured and unstructured. This effectively includes all data and information that can be used – whether (a) a database of customers (and their preferences plus their previous purchases) for personalising answers,  (b) Q&A lists (for recognising questions and ‘intent’ as well as the sending the right answers (c) data readiness.

Establishing information & data readiness for chatbot is a critical step in any AI (or even CRM project).   Is your data ready to be used (is it clean and consistent in, say, the use of first name, second name with first letter in capitals, plus does every customer list the type of washing machine they bought?) etc. If the data is not OK – you may need dozens of people cleaning it up. This can take weeks or even months. However – if everything is OK, you may need no more than a handful of people in total.

Data Readiness is more complex than capital letters for names. It means that data is ready to be used at different levels and angles:

1. Accuracy – is any data we provide correct, consistent, cohesive, always up-to-date and owned by us?
2. Security – can data access be misused to breach our network? Accessibility – chatbot is given access to read, write, modify and create content (access includes diaries)
3. Compliance – are we only displaying data that is needed?
4. Technical – is accessing the data actually possible?

MegaData – ensure all the data and information is ready for the chatbot to communicate to users. This includes Conversation Flows/Decision Trees.

Security  –  protect your business from ‘malicious intents’ (a) hackers accessing your data (b) attacks from say an aggressive competitor 10,000 enquiries per second which creates –   DDoS (Distributed Denial of Service) = system overload = systems crash.  There are 7 layers of security including network security, application security and data security.

MINUTES  / TIMESCALES   how long does it take to get a chatbot up and running?  Again depending on the solution you want to see after completion. And how fast you want things done. So using a basic project framework setup triangle might bring everybody in alignment (resource & scope & cost à Quality). In uncertain/ambiguous situations like these – going agile for execution is the best option.  Set an exact number of hours p.w. on this project.  Assign people and say “GO! See what you can do with the money we have in 12 months”.

Incidentally, Speed of Bot-Response should be agreed: 3-5 seconds or instantaneous + volume of enquiries/interactions from visitors (5 an hour or 500,000 a day) affects costs & solution design and architecture.

—end—

Many thanks to Tom Sickert. This is an early draft and so we welcome your comments, queries, challenges or improved examples. Please do post a comment.

If you liked this you might also enjoy:

Chinese GirlBot With 465m Boyfriends

Artificial Influencers – Meet Shudu & Miquela

Artificial Influencers Use My Magic Marketing Formula (IRD)

Here Come The Really Clever Bots – where AI meets customer needs

Join me in Clubhouse in my club called SOSTAC® Plans any Friday 3.30pm – 4.00pm BST for a chat, Q&A, observations about SOSTAC(r) Plans and any other marketing related issues including AI Driven Bots.

The post Develop your own Chat-Bot – SOSTAC® Project Plan appeared first on PR Smith Marketing.

The post appeared first on PR Smith Marketing.

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At last, here are the checklists – what you got to do to ensure you are GDPR compliant. Part 3 now explores GDPR Tactics (the details of Strategy Part 2) and the Actions (including checklists you can use) and finally, Control – what you need to check to ensure your data is safe and fully under control.  Part 1 introduced GDPR Situation which is a shock for many businesses, as it could put some out of business!

TACTICS (the details of strategy)

To START MANAGING DATA MUCH MORE SERIOUSLY employ these Tactics

Appoint a Data Officer

Medium to large businesses will need a data protection officer.

Audit High-Risk Aspects Of The Business

Businesses must identify very high risks and how they would mitigate it. If your data is encrypted, then it is not ‘high risk’.

Commence Data Protection Impact Assessments (DPIAs)

issued in 2017 as part of the implementation package for the General Data Protection Regulation (GDPR)

Run An Attack Simulation

with senior management to ensure that all of your data processes are robust in the case of an attack or a personal data breach and are GDPR complaint.

Run an attack simulation

Document Your Risk Management

Organisations and accountable individuals must document their approach to managing risk inherent with collecting & keeping personal data that your firm, your partners and your suppliers process.

To BUILD A DATA PROTECTION CULTURE – employ these Tactics:

Train Staff 

Ensure all your staff (from Board Level down) have regular data protection awareness training (see  ‘internal marketing’ in the Action section). Training is the first line of defence. Did you train your staff and your board? Board members need to be aware of the business risks of cyber security and understand the legal significance of an accountable individual at Board level.

Laurette Batstone SOSTAC® Certified Planner

Encrypt Data

Data encryption translates data into another form, or code. Only people with access to a password or secret key (formally called a decryption key) can actually read it. Encrypted data is commonly referred to as ciphertext, while unencrypted data is called plaintext.

Improve Response Times When Reporting Hacks 

Under GDPR you have 72 hours to report a breach of security to the ICO (compared to the old 138 day response time) .  GDPR will become part of the value chain.  Businesses will have to integrate GDPR into almost everything as everything becomes connected via the IoT (Internet of things).   

Improve Response Times When Reporting a Hack

Improve Response Times SARs

Subject Access Request ( a request from a customer to see what data is being kept about them) is free of charge and organisations must complete this within one month, except in exceptional circumstances, where multiple requests are made, a ‘reasonable’ administration fee can be charged.

Regularly Scrutinise Your Cloud And Server Suppliers

You have a responsibility to check up on your suppliers and any partners that they too are compliant with GDPR.

Induction & Data Protection

Include data protection into induction processes.

Digital Data is a new asset which needs to be managed carefully

ACTIONS (how to ensure excellent execution of the new GDPR)

Internal Marketing

Internal Marketing means Motivating, Communicating and Training your team to ensure they execute GDPR with excellence and with passion.

This can come down to specifying detailed actions (checklists of things individuals have to do).

Once all stuff fully understand why GDPR is important (find out how to motivate them), then communicate with them about the importance and ultimately train them to point where you even issue fool-proof checklists for procedures or processes. Remember, training is mandatory. So, schedule a series of motivation & communication & training events across the organisation. In marketing parlance, we call all of this Internal marketing (motivating staff, communicating with staff and training staff). It’s often forgotten (& requires a budget) & is often the hidden reason why so many plans fail.

Motivate, Communicate & Train your staff

Motivation:

Ensure staff and board members understand how important GDPR is. Ensure they understand the ethics and the reasons why we need to protect our children, our families and our firends from data abuse as well as the scale of fines (and prison sentences). Ensure they understand the benefit of keeping clean and secure data. Incentivise employees to spot and fix or report any errors made in data processing.

Communications

Communicate to all staff – from Board Level down to operators, the importance of GDPR.  Make it part of all regular reporting so that meetings at every level have GDPR on the agenda. Create and refer to Data KPIs.

Training

Anyone handling personal data is now legally obliged to be trained (under the GDPR). Staff must be trained so they understand the 6 basic data protection principles (article 5):

1. Consent – did you get consent? Processed lawfully, fairly and in a transparent manner in relation to individuals
2. Purpose – was the data collected for specified, explicit and legitimate purposes
3. Adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed
4. Accurate and, where necessary, kept up to date
5. Kept in a form which permits identification of data subjects for no longer than is necessary
6. Processed in a manner that ensures appropriate security of the personal data

Source ICO (Information Commissioners Office)

Can you prove that you are compliant with GDPR?

Remember: The Burden of Proof Is On The DC

Under the GDPR the burden of proof is on the DC (Data Controller) to verify that it received lawful consent.

• It must be clearly distinguishable from other matters.
• Data Privacy Notice needs to be intelligible, easily accessible and in clear and plain language.
• It must be as easy to withdraw consent as it is to give it.
• If a service to be delivered is conditional on providing consent to personal data processing, then that consent isn’t deemed to be ‘freely given’ and isn’t valid.

Ardi Kolah, Henley Business School

12 Steps/Actions Preparing for GDPR (ICO )

Security of data is a critical factor

Source: unknown
 

How To Create GDPR-Compliant Consent Forms

• Request as little data as possible
• Make the terms and conditions clear
• Make it easy to withdraw consent
• Use a double opt-in mechanism‘

Source: IT Governance

A double opt-in mechanism stops individuals from giving their consent by mistake. The first step involves a regular opt-in tick-box (consent form).  This is followed by an automated email with a link that they need to click on to verify, or confirm, their consent.

CONTROL

Are you in control of your data?

Here’s 7 Data Protection Questions To Answer Before Some Banks Will Do Business With You

Data assets can become toxic if not adhering to GDPR. Gilbert Hill founder, One Trust, revealed that one bank told him that they won’t ‘do business with you unless you can tell me:

1. How you collect data?
   2. How you use it?
   3. How you protect it?
   4. How you secure it?
   5. How you clean it?
   6. How you give it back to users?
   7. How you check it every six months?

It is recommended that you clean up your data regularly (Gilbert Hill recommends every 6 months & suggests ‘It can be less risky to bin data and start again’ (rather than keeping unclean data).   All of this is simply good customer service and excellent marketing practice. GDPR ultimately protects and improves the CX (customer experience).  So if you really care about your customers, you should embrace GDPR with open arms.

GDPR Responsibility starts with the board of directors and works across the organisation everyone’s responsibility [image reproduced with kind permission of Henley Business School]

Another 6 Questions to check you are in control of your customers’ personal data

John Culkin, Director of Information Management, Crown Records Management highlights these 6 ‘must-have’ answers regarding customer data:

1. What you have?
2. Where is it?
3. Where are you sending it?
4. Why do you have it (what do you do with it)?
5. What form is it in?
6. How long do you need to keep it?

2 Crunch Questions

Can you prove that you have collected data legally and morally?

Can you prove that it is secure?

Other Regulators (beyond the ICO)

The ICO won’t be the only regulator involved. FCA, the Environment Agency, General Pharamaceutical Council, Ofcom, CMA, Care Quality Commission and many more.

Summary

So there you have – SOME of the details of GDPR. We have looked at some  GDPR Tactics you must employ, followed by SOME more detailed action checklists and finally to ensure you are in control of your GDPR destiny, we looked at some of what you need to monitor and control. Part 1 introduced GDPR Situation which is a shock for many businesses and Part 2 explored Strategy. Embracing GDPR means protecting and caring for your customers’ personal data and this is a good thing. This will help to build a powerful data asset that help your organisation to fulfil its goals. The future looks bright when you embrace GDPR.

The future looks bright when you embrace GDPR

Thanks to

Many thanks to Ardi Kolah, Henley Business School for the inspiration.

Please note this blog post is not a comprehensive set of legal guidelines. To complete your GDPR preparation, we advise you to check your local Information Commissioner Office or your Data Protection Commissioner.

Further Information

Information Commissioner’s Office (UK)

Data Protection Commissioner (Irl)

If you enjoyed this you might also enjoy:

Part 1 GDPR:  Opportunity to Boost CX or a Threat of Closure?

Part 2 GDPR: Objectives and Strategy

How Trump Won by analysing data to deliver extremely relevant and highly targeted messages that worked.

How To Write The Perfect Plan in 4 minutes using the SOSTAC ® Planning Framework (4 min. video)

References

Armstrong, Jonathan (2017) Cordery: ‘All you need to know about GDPR but were too afraid to ask’, GDPR Conference Europe, 27 Apr

Cameron, Gareth (2017) ICO: ‘The pathway to implementation’, GDPR Conference Europe, 27 Apr

Kolah, Ardi (2017) Henley Business School: Sizing the risk – carrying out a data protection impact assessment Lite

Miller, Nigel (2017) Fox Williams:  Individuals’ Rights Under The GDPR, GDPR Conference Europe, 27 Apr

Smith, PR (2018) SOSTAC^® Guide to your perfect digital marketing plan

SOSTAC^® Portal for SOSTAC^® Certified Planners

Thanks to 

Ardi Kolah, Executive Fellow & Programme Co-Director, GDPR Transition Programme, Henley Business school, University of Reading.

Nick James, CEO of Amplified Business Content, hosts of GDPR Europe Conference

Ruairi Thomas, MD, DST Systems for the gold-fish observation!

The post GDPR Tactics Action & Control (Part 3) appeared first on PR Smith Marketing.

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Is GDPR (General Data Protection Regulations) an opportunity to boost CX (Customer Experience) or a threat that could put you out of business? It’s both. A great opportunity, if you work with it. A threat, if you dare to ignore it. You’ve only got until 25th May 2018 before it is fully applicable in the EU and elsewhere. We’ll use the SOSTAC^® Planning framework to help you plan for your own GDPR adoption.

PR Smith’s SOSTAC^® planning framework is used around the world by both blue chips and start-ups to write business plans, marketing plans, digital marketing plans, campaign plans, project plans, health & Safety plans, digital transformation plans, and now, GDPR transformation plans. Voted in the Top 3 Business Models around the world by the Chartered Institute of Marketing’s Centenary Poll, SOSTAC^® has recently by adopted by Linkedin and KPMG Digital HQ and an array of other organisations as their preferred planning framework. It’s popular because of its simplicity and solid logic.

PR Smith’s SOSTAC® Planning Framework

Situation Analysis means where are we now?’

Objectives – where do we want to go?

Strategy – how do we get there?

Tactics – the details of strategy

Action – how to ensure excellent execution (internal marketing)

Control – how do we know we are getting there.

+  the 3Ms: the 3 key Resources Men (men and women – the human resource), Money (budgets) & Minutes (timescales)

Here’s PR Smith’s 4 minute SOSTAC^®summary on video. Let’s have a look at how SOSTAC^®  help you to prepare for GDPR.

SITUATION

Data is the Lifeblood of Any Business

Data can give you competitive advantage. Data (or lack of) can destroy a business. How long could you continue without access to your data? So data is the life blood of any organisation. Data is also deemed to be the most valuable resource in the world (more valuable than oil) states The Economist (see Part 2).

Do We Really Need General Data Protection Regulations?

The answer is ‘yes’ and here’s 6 big reasons why:

1. Falling Customer Trust (with their personal data)

Yet only one in four adults trust businesses with their information. UK adults fear sharing their information for marketing as much as sharing with criminals (Garreth Cameron, ICO 2017).

2.  Data Criminals Are Growing

Con-men, criminals, and even hackers see opportunities online. Many of the opportunities are in the form of data. Irresponsible organisations, sloppy organisations and unethical organisations all help potential criminals to exploit your data, your identity and possibly your money.  There is a global increase in cyber attacks. Hackers are everywhere, preying, probing, testing, pushing, waiting for a brief drop in security. And now that IoT is here (the Internet Of Things), it just takes one weak link in a chain of connected devices to give hackers access – watch your kettle in the kitchen!

Hackers are waiting for just one momentary lapse in security

The world’s largest reported hack was Yahoo (2013).  Yahoo lost $1 billion share value because of poor security (Jonathan Armstrong, 2017).

40,000 TESCO bank accounts were hacked with money disappearing from 20,000 of them (Ardi Kolah, 2017).

Equifax hackers access 143m US consumers (McLannahan & Cornish, FT 2017)

Mobile operators now report 210,000 accounts were hacked (not 133,827) as reported to CIO Nov 2016 (Ardi Kolah 2017).

Global Increase In Cyber Attacks (image courtesy of Henley Business School)

Lawrence Tracey (Data Specialist in Vancouver) says ‘Did you know the easiest path for a hacker to get through the corporate security is via an employee’s car? Cars are easy to hack into; you just have to do a quick scan of YouTube to see a frightening list of possibilities. Most of them show a hacker taking control of a car, however, many people have their smartphones set to auto connect to their car and to auto connect to their home network and the corporate network when in the office. Speaking of the office, the printer is deemed to be the most vunerable access point to a business system (see the frightening Wolf ads)

https://youtu.be/DkajtSOAyec

Christian Slater as the chilling Wolf revealing the importance of network security

3. GDPR Breach (Poor Data Security) Incurs Big Fines

€20 million or 4% of global turnover for primary infringement (if it impacts a data subject/individual) or €10 million or 2% set for secondary infringement (a breach of the regulations e.g. not carrying out technical and organisational measures as required) – whichever is the greater. We can also be compensated for stress, for data loss, for identity theft, from funds being stolen and or a class action suit. There are exemptions for companies with less than 250 staff.  Subject to the nature of the personal data breach /infringement of the GDPR, the Data Controller, Joint Data Controller or Data Processor could be subject to a financial penalty of up to 4% of global turnover of the preceding year or €20m (whichever is the greater).

The sanctions and fines can apply to both the Data Controller, Joint Data Controller and the Data Processor. “Remember there’s now under the GDPR,  joint and several liability” (Ardi Kolah 2017).  Note: Media Tactics (UK) were fined £270,000 and more recently, Keurboom Communications (UK),  £400,000 fine (May 2017) for breach of privacy with nuisance telephone calls.

A £400k fine means a company (with 10% margins) must find £4m extra sales to cover this loss.

 4. GDPR Breach Can Close Your Business

You can be forced to stop processing personal data i.e. it can stop your business. ‘ICO has the power to order temporary or permanent ban on personal data processing.’ In the UK, the ICO has the power to order temporary or permanent ban on personal data processing.  Very detailed contractual arrangements are now required between DC (Data Controller) and DP (Data Processor). In fact, all contractual arrangements extending past 25 May 2018 need to be GDPR compliant.

A breach of GDPR could kill your business

5. GDPR Breach Can Send You To Prison

You can go to prison for both a breach (of security) and also for non-compliance with GDPR i.e. even if you don’t suffer a breach, if you are inspected and found not to be GDPR compliant, they can go after you.  ‘Under the GDPR, Member States have powers to bring in criminal sanctions for failure to comply with the GDPR. This will apply where there are serious infringements and where the accountable individual at Board level is responsible as Data Controller’ (Ardi Kolah 2017).

A breach of GDPR could send you to prison

6. GDPR Protects Individuals & Your Customers

This should really be the number 1 reason. Genuinely customer centric businesses will list this as the number one reason.The General Data Protection Regulations protects individuals and their private data. It came into force 24^th May 2016 (ie it was adopted by the European commission) and after a two year transition period, it becomes fully applicable 25th May 2018 across all 28 EU member states (UK is supposedly adopting EU laws). Are you ready? 

Adhering to GDPR can improve customer trust

Everyone Has Rights Under GDPR

Personal Data includes: genetic data, bio data, voice data, finger prints and recognition data, CCTV, photos, recorded calls, CRM and after sales, search strings, web reports systems log IP addresses, accounts and finance, financial records, HR records, communications tools such as emails messenger messages, social networks and marketing databases and profiles*.

Customers have rights.

Customer Rights

Consent means that the customer freely gives his/her information and is informed of why it is being collected.

This should be documented and verifiable.

Data should be easy to find and easy to withdraw (if an individual, or ‘subject’ requests this).

Collecting & using data should be legitimate. NB using data for marketing may not be legitimate (unless you explicitly explain how it will be used e.g. to send you weekly emails).

Rights to information: transparency; concise policies in plain language; accountability; individual rights; Subject Access Request (SAR) is free of charge must be completed within one month.

• Right to rectification: if data is inaccurate or incomplete.
• Right to object to the Marketing Profiling and automated decision-making.
• Right to data portability. Can get a copy that other companies can use in the required format. Provide all data in a format which third-party companies can easily process.
• Right to erasure (the ‘right to be forgotten’)

Customer Rights: Nigel Miller, Fox Williams, Individuals Rights

The right to be forgotten. Customers can ask for their data to be erased, wiped out or ‘forgotten’.

Essentially, GDPR requires ethical capture and ethical use of all customers’ personal data.

GDPR Applies to Every Organisation

GDPR applies to both B2C and B2B businesses and organisations established in the EU either as a Data Controller (DC) or a Data Processor (DP).  It also applies to ‘non EU DCs & DPs that offer goods or services in the EU (or who monitor the behaviour of individuals who are in the EU’) Ardi Kolah, Henley Business School.

GDPR even applies to robots – well if you consider Artificial Intelligence to be at the heart of robotics (more on AI and Robotics).

Accountability goes all the way up to the CEO.

GDPR Opportunity or Threat?

Some companies will go bust because of it. Some companies will see it as an opportunity to create/strengthen competitive advantage by improving the CX (Customer Experience) & adopt world-class marketing standards in data collection & protection, that reassure and satisfy customers.

Now It Is Easy To Report A Nuisance Call or Message 

It is getting easier for customers to complain about how they are being harassed by =nuisance phonecalls and spam emails. Here’s how easy it is in the UK to complain via the Information Commissioners Office (ICO).

ICO Tips on how to complain about misuse of your personal data

Summary

So there’s the Situation Analysis – customers, courts and regulatory bodies are tired of personal-data mis-use, or even sloppy personal-data management. So, manage your data very very carefully as neither customers nor courts will forgive you for any breaches of GDPR. Part 2 addresses setting your Objectives (where do you want to go with GDPR) and Strategies (how you are going to get there) i.e. to help you to plan to embrace GDPR in your business. Part 3 will look at the Tactics (the details of strategy), Actions (required to ensure excellent execution of GDPR) and finally, Control (how do you know you are always fully compliant with GDPR).

References

Armstrong, Jonathan (2017) Cordery: ‘All you need to know about GDPR but were too afraid to ask’, GDPR Conference Europe, 27 Apr

Cameron, Gareth (2017) ICO: ‘The pathway to implementation’, GDPR Conference Europe, 27 Apr

Kolah, Ardi (2017) Henley Business School: Sizing the risk – carrying out a data protection impact assessment Lite

Miller, Nigel (2017) Fox Williams:  Individuals’ Rights Under The GDPR, GDPR Conference Europe, 27 Apr

McLannahan, B. &  & Cornish, C. (2017) Equifax hackers access details of 143m US consumers, FT 8 Sep

Smith, PR (2017) SOSTAC^® Guide to your perfect digital marketing plan

SOSTAC^® Portal for SOSTAC^® Certified Planners

Thanks to 

Ardi Kolah, Executive Fellow & Programme Co-Director, GDPR Transition Programme, Henley Business school, University of Reading.

Nick James, CEO of Amplified Business Content, hosts of GDPR Europe Conference

If you enjoyed this, you might also like:

GDPR Opportunity or Threat To Your Business? (Part 2)

How Trump Won by analysing data to deliver extremely relevant and highly targeted messages that worked.

How To Write The Perfect Plan in 4 minutes using the SOSTAC ® Planning Framework (4 min. video)

The post GDPR (General Data Protection Regulations) – Opportunity to Boost CX or a Threat of Closure? (Part 1) appeared first on PR Smith Marketing.

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Continuing from How Trump Won – part 1 – SOSTAC ® Analysis, where we looked at the first three stages of the plan: Situation Analysis (where was Trump?); Objectives (where did he want to go?) & Strategy (how was he going to get there?), now let’s explore Tactics (the details of strategy); Action (how to ensure excellent execution) and Control (how do we know we are getting there?). In particular, we’ll explore how he used, what I call, the Magic Marketing Formula to win.

PR Smith’s SOSTAC® Planning Framework www.SOSTAC.org

Tactics

Tactics include the marketing mix and this includes the communications mix. So whether it is a facebook ad, a social media post or tweet, a conference speech or any tactical tool, the key (apart from targeting) is to ensure the right message is shared (or ‘reflected to the audience’). This is, what I call, the Magic Marketing Formula.

The Magic Marketing Formula – IRD

The Magic Marketing Formula: IRD

Here it is: Identify (needs); Reflect (those needs with solutions or sometimes just slogans) back to your audience; Deliver (a reasonable product or service).

Make America Great Again = Magic Marketing Formula

Let’s start with the general message (the slogan that was used everywhere). This was shared (or reflected back to all audiences).  We will look at other, more specific messages, including ‘dark posts’, sent exclusively to very specific audiences (that others could not see easily as they targeted discrete audiences after they had profiled the personality of every adult in the USA – 220 million profiles). More on this in Part 3. But, first, let’s look at Trump’s slogan.

“Trump’s ‘Make America Great Again’ was designed to make white working-class men remember when things were better for them or, at least, they thought they could remember.” Stephen Greyser, professor of marketing at Harvard Business School    Fottrell (2016).

‘Make America Great Again’ has a certain ‘darkness at the edge of that slogan as there is (also) a darkness at the edge of ‘Take Back Our Country’ (the Brexit Leave Campaign) & yet there’s also a glimmer of a legitimate & important aspiration in both of those slogans. … …. the legitimate aspiration underlying those slogans has to do with a sense of national community’ (Harvard’s Professor Sandel 2017). Trump addressed the people’s anger. Perhaps Clinton assumed the anger was against immigration and trade, and at the heart of that, is jobs. ‘But it’s also about even bigger things., about the loss of community, disempowerment, & social esteem (a sense that the work that ordinary people do is no longer honoured & recognised (& rewarded).’ Sandel (2017). So the need for community (national community), amongst other needs is reflected back through the consistent use of the slogan. Therefore appealing to hidden needs, needs that perhaps, many voters weren’t even conscious of during their voting. 

Professor Michael Sandel, speaking at Davos 2017

Professor Sandel continues: ‘The language of patriotism has been appropriated by the right for the most part. There’s no reason why centre-left parties can’t reclaim and articulate their own conception of national purpose, national community and shared identity & patriotism. What the elite missed was the sources of the anger & resentment that has lead to the populist upheavals in the US & Britain & many other parts of the world.

Pavlovian Conditioning?

Although Trump is part of a different establishment (business establishment) swing voters seemed to accept his carefully controlled positioning as a non-establishment politician (see part 1: Positioning) . Perhaps a Pavlovian conditioning – repeating the same message again and again and after a while his audience believed this, despite seeing Trump flying around the country in his “Trump” branded 757 plane. Perhaps because by doing so he showcased an aspirational lifestyle that appealed to white, working-class Americans (NB the magic marketing formula: identify needs/aspirations – reflect them back, ironically, via your own mobile media/your own private jet).

Is it possible that Donald Trump conditioned voters just like Russian physiologist, Dr. Ivan Pavlov, conditioned dogs back in 1902? www.PRSmith.org/SOSTAC

Tactics: Proposition: ‘Change’

The promise of ‘change’ worked for Obama previously & this time it worked for Trump too. Interestingly, both Trump and Obama (in previous Obama campaigns) identified that many people still want change.  Obama promised it in a positive light ‘whilst Trump used anger to get it across’ (Kanski 2016). However, this time, Trump went after the disenchanted relentlessly and rammed home his message of ‘angry change’.

“In the end it was a clear-cut message: If you’re happy with the status quo, vote for her; if you want change, vote for me,” said Dan Scandling, senior director of public affairs at APCO Worldwide. “That was what resonated.”
“She (Clinton) never effectively communicated how she was going to make people’s lives better beyond hanging her hat on the last eight years,” says Aaron Gordon, partner at Schwartz Media. (Kanski 2016).

Clinton’s more rational (and longer) economic and social arguments might have missed the attention span of those swing voters, as did the ‘Remain’ campaign in the UK’s now notorious Brexit referendum. Lord Heseltine (former UK Deputy Prime Minister under John Major and Secretary of State under Margaret Thatcher ) summed up short attention spans, lack of facts and policies, when referring to the UK’s Brexit, he pointed the finger at one of its ‘Leave Campaign’ leaders who has since become the UK’s foreign minister, Boris Johnson, and said:

“How convenient to substitute a slogan in place of arguments you have not got.”  (Rogers 2016)

As our attention spans have shrunk from 42 seconds in 1960 (see How Trump Won part 1) to 5 seconds in 2008 and now 4 seconds, the words of John C. Maxwell (‘leadership’ author) resonate more profoundly:

John C Maxwell (leadership author)

Proposing What Audiences LikeTo Hear (IRD)

‘What that translates into is a constant iterative process whereby he (Trump) experiments with pushing the conversation this way or that, and he sees how the crowd responds. If they like it, he goes there. If they don’t respond, he never goes there again, because he doesn’t want to be boring. If they respond by getting agitated, that’s a lot better than being bored. That’s how he learns….. In that sense, he’s perfectly objective, as in morally neutral. He just follows the numbers. He could be replaced by a robot that acts on a machine learning algorithm’ (O’Neil 2016).

Through data analysis (big data) Trump was able to send different messages to different groups of voters with different needs. ‘Cutting immigration’ or “draining the swamp” of corrupt or incompetent politicians and bureaucrats – messages were targeted only at those that connected with these messages. (I’m going to have to do a Part 3 to explain how this worked).

‘Once up and running at the end of the summer, it was soon sending out tailored messages to 100,000 targeted voters every day’ (Marr 2017).

See the BBC video in Part 1 that explains exactly how Cambridge Analytica analysed the adult voting population of America (without them knowing their data was being used in this way) and subsequently targeting precise ads to each personality type telling them just what they wanted to hear.

Proposition, Message Credibility & Messages

Trump reached many disenchanted blue collar male voters by reflecting his messages in their language e.g. by ‘talking about the world and globalism in terms of winners and losers,’ Eric Bovim (Kanski 2016). Not everyone can understand social economics, but everyone understands the concept of winners and losers. Short. Simple. And not weighed down by actual facts or policies.

Having said that, if a significant proportion of the voting population do not want to hear long-winded arguments, then Trump just applied the Magic Marketing Formula (IRD) again and again, by keeping it short, tapping into fears and emotions, reflecting keywords that connect, but avoiding detail at all costs.

Trump Is A ‘Meaningfully Different Brand’

‘Meaningfully different brands’ are much more likely to be selected, to command greater premiums and to grow in the future,” says Christopher Murphy, chief client officer at brand analysts, Millward Brown North America.

Q1 Does the candidate meaningfully connect – either functionally or emotionally?

Q2 Is the candidate seen as different or capable of driving positive change?”

Trump, Murphy concluded, did both (Fottrell 2016).

Tactical Tool –  twitter

Trump’s preferred vehicle to spread his message was largely his Twitter feed. He built his momentum on Twitter, spreading the #MakeAmericaGreatAgain or #MAGA hashtag widely.  12 million followers (9 Nov –  now 16.4m)
Clinton’s Twitter feed (11.4m) felt more traditional and political (Kanski  2016). Clinton’s slogan ‘Stronger Together’ did not generate nearly as much traction. It is possible to predict which tweets/messages will get the most retweets (see IBM twitter analysis). Though I could have forecasted ‘Stronger Together’ was limp and wouldn’t gain much traction.

Tactical Tool –  Targeting Facebook Ads: 1,000% Increase in Sales

Jared Kushner (Trump’s son in law) who set up the stage 2 Strategy (see Part 1), database decision making and highly targeted facebook ads (& other cable TV targeted ads), also quickly learned how to continually refine the targeting of facebook ads. See 200 variables available to target specific messages. In fact, he quickly increased the sales of Trump merchandising (e.g. baseball caps with ‘Make America Great Again’) from $8,000 to $80,000 per day – ‘simply by refining the target demographic’ (Marr 2017).

ACTION

Build A Campaign Team 

Soon, Jared Kushner, was assembling a speech and policy team, handling Trump’s schedule and managing the finances.

Build A Data Centre

As mentioned in Part 1, within three weeks, in a nondescript building outside San Antonio, Kushner built what would become a 100-person data hub designed to unify:

• fundraising
• messaging
• targeting

They also tapped into the ‘Republican National Committee’s data machine, and it hired targeting partners like Cambridge Analytica to map voter universes and identify which parts of the Trump platform mattered most: trade, immigration or change’ (Bertoni 2016) . Forbes reported: ‘Tools like Deep Root drove the scaled-back TV ad spending by identifying shows popular with specific voter blocks in specific regions–say, NCIS for anti-ObamaCare voters or The Walking Dead for people worried about immigration.

Kushner built a custom geo-location tool that plotted the location density of about 20 voter types over a live Google Maps interface.’

Kushner built a custom geo-location tool that plotted the location density of about 20 voter types over a live Google Maps interface

Very quickly data determined decisions, so just like Teddy Goff and previous Obama campaigns, data dictated almost every campaign decision including:

• travel
• fundraising
• advertising
• rally locations
• topics of the speeches

Big Data is everywhere

Build A Disruptive Start-Up Culture

Kushner was unschooled in traditional campaigning, he was, therefore, able to look at the business of politics in the same way that so many entrepreneurs analyse and attack other bloated industries.

Learn Rapidly

Kushner knew what he needed to know. He knew what he needed to learn and learn it quickly. So in Kushner’s own words: “I called some of my friends from Silicon Valley, some of the best digital marketers in the world, and asked how you scale this stuff? They gave me their subcontractors. I had them give me a tutorial on how to use Facebook micro-targeting.” Synched with Trump’s blunt, simple messaging, this would go on to work very well.

Constant Beta Testing 

Constant beta Testing = Constant Learning = Constant Improvement. Trump was selling $8,000 worth of hats and other items per day. Bit by bit Kushner learned how to improve this with better targeting via facebook ads.  Once they found something worked – they scaled it up. Result: sales grew from £8k to $80k per day thus:

• generating revenue
• expanding the number of human billboards

Constant Beta Testing requires a cultural shift which, in turn, requires constant monitoring and control (see ‘Control’ section). 

No Fear Of Failure 

The entrepreneurial spirit / disruptive start-up culture ensured that there was no fear of failure just a hunger for fast improvement & scalability.  “We weren’t afraid to make changes. We weren’t afraid to fail. We tried to do things very cheaply, very quickly. And if it wasn’t working, we would kill it quickly,” Kushner says. “It meant making quick decisions, fixing things that were broken and scaling things that worked.” (Bertoni 2016).

“We weren’t afraid to fail.” Kushner

Scale Up What Works  –  Tailor Targeted Ads

Scale What Works & Stop What Doesn’t – quickly.  Ineffective ads were killed in minutes, while successful ones were scaled up. Trump’s team ended up sending more than 100,000 uniquely tweaked ads to targeted voters each day.

Use Machine Learning 

Machine learning helped to boost their fundraising efforts. Kushner installed digital marketing companies on a trading floor to make them compete for business. If anyone has more information on how Donald Trump’s team used machine learning, please do let me know, as I will be doing a Part 3 about Big Data helped Trump to win. 

Control

Sales Revenues & Donations 

The Trump team monitored revenues every day. The campaign raised more than $250 million in four months–mostly from small donors. They kept monitoring and learning what worked best and then scaled up.

Constant Real-Time Analysis 

Constant up-to-the-minute voter data, provided both ample cash and the insight on where to spend it. ‘When the campaign registered the fact that momentum in Michigan and Pennsylvania was turning Trump’s way, Kushner unleashed tailored TV ads, last-minute rallies and thousands of volunteers to knock on doors and make phone calls’ (Bertoni). See Part 3 (‘How Big Data helped Trump’.

Ask Great Questions

Kushner asked this seemingly basic question which really focussed the campaign team’s minds: “How can we get Trump’s message to that consumer for the least amount of cost?” FEC filings through mid-October indicate the Trump campaign spent roughly half as much as the Clinton campaign did (Bertoni 2016).

Monitor Bangs For Your Buck

Kushner even spent $160,000 to promote a series of low-tech Trump policy videos which generated more than 74 million views which equated $2 CPT (Cost Per Thousand people reached). In addition to getting more cost effective, Kushner was learning which video messages worked best.

Constant Beta Testing

“We played Moneyball, asking ourselves which states will get the best ROI for the electoral vote,… Kushner

Monitor Twitter Streams 

Using 3,000 tweets from Trump and 3,000 from Clinton, here is Trump’s most frequently used words visualised in a word-cloud:

Trump’s Word Cloud identifying his most frequently used words

Here is Clinton’s most frequently used words:

Clinton’s Word Cloud identifying her most popular words

Trump’s most common words used in his tweets were positive (i.e., great, will, thank, as well as the hashtag #MAKEAMERICAGREATAGAIN). These all have positive meanings. Clinton’s most frequently used word on Twitter was trump (NB lower case disrespect!). What does this tell you?

Incidentally, it is possible to predict how successful* a tweet will be (or predict the performance of a selection of tweets and thus select the best one to send). * One success criteria is the number of retweets forecasted (within a certain level of confidence) Cortana 2016. If you enjoy data mining, you might enjoy this from Microsoft’s machine learning people. Everything generates feedback and learning, which is fed back into the system to update the situation analysis, refine objectives, inform strategy and tactics as you can see in the diagram below.  part 3 will explore how door-door canvassers fed back data regarding which message worked best for each household.

Control monitors and collects feedback which is constantly used to update all other sections of a SOSTAC® plan.

In the end….

crystal clear positioning and targeting driven by clever use of data layered on top of the Magic Marketing Formula combined with a ‘disruptive start-up’ attitude’ always ready to learn and constantly improve every hour – delivered Trump, the outsider, the most unexpected of wins (despite winning less than 2 million votes than Clinton). As Forbe’s Bertoni reports:

‘If the campaign’s overarching sentiment was fear and anger, the deciding factor at the end was data and entrepreneurship.’

‘Trump looked at the US and correctly saw an anxious populace that was ripe for facile answers, scapegoats and a narrative of unjust victimisation. So he pounced.’ Frank Bruni, New York Times, 14 Dec 2018

—

See How Trump Won part 1 – Situation Analysis, Objectives and the critical Strategic choices (the BBC video explaining how Cambridge Analytica analysed a nation of voters).

You might also enjoy How Obama Became America’s First Black President

You might not enjoy, but perhaps need to read:  The Dark Arts Of Marketing – Breaking Down Society to Create a New Culture – Using Data & IRD

How SOSTAC® Works – a 4 minute video by PR Smith

How SOSTAC® Works – a 4 minute video by PR Smith

Become a SOSTAC® Certified Planner  visit www.SOSTAC.org

The SOSTAC® Guide to your Perfect Digital Marketing Plan

The new SOSTAC(r) Guide for Digital Marketers

Sources:

Bertoni, S. (2016)   How Jared Kushner Won Trump The White House , Forbes December 20

Cortana Intelligence & Machine Learning (2016) Data Mining the 2016 Presidential Campaign Finance Data, Cortana Intelligence and Machine Learning Blog, 10 Oct

Economist (2016) The post-truth world: Yes, I’d lie to you, 10 Sep

Flood, A. (2016) ‘Post-truth’ named word of the year by Oxford Dictionaries, The Guardian, 15 Nov.

Fottrell (2016) How TV reality star Donald Trump won the election with his ‘disruptive’ brand, MarketWatch.com 11 Nov.

Grassegger, H. & Krogerus, M. (2017), The Data That Turned the World Upside Down, Motherboard, 28 Jan

IBM (2016) Trump and Clinton may have used some Machine Learning, DataScience.ibm.com , 21 Dec  http://datascience.ibm.com/blog/election-2016-data-analysis/

Kanski, A. (2016) Change and authenticity: The messages that won over American voters, PR Week 09 Nov.

Marr, B. (2017) Why Big Data Wasn’t Trump’s Achilles Heel After All, Forbes 9 Feb

O’Neil, C. (2016) Donald Trump is like a biased machine learning algorithm, Mathbabe.org 11 Aug

Rogers, D. (2016) The Politics of Fear, in an interview with Lord Heseltein, PR Week, April 2016.

Sandel, M. (2017) ‘ Why The Democrats are so out of touch with the People‘, World Economic Forum, Davos 2017 – (a very interesting video).

The post How Trump Won (Part 2) – using the Magic Marketing Formula – a SOSTAC Planning Analysis appeared first on PR Smith Marketing.

—

Many are still wondering how Donald Trump became president of the United States Of America, despite himself? Here’s an analysis, using SOSTAC^® Planning Framework to explore some of Trump’s plan and to give some insights into his subsequent successful campaign. Comments are most welcome. Situation analysis (where are you now) , Objectives (where are you going?), Strategy (how do you get there?), Tactics (the details of strategy), Action (how do you ensure excellent execution) and Control (how do you know you are getting there – what will you measure?). I will use these to categorise various aspect of the Trump campaign but please remember this is just an outline not an in-dept detailed analysis.

PR Smith’s SOSTAC® Planning Framework

Situation Analysis

Customer Analysis

Who – are Trump’s potential voters?

Trump focused on “left-behind” voters, specifically white working-class men (and women). He initially gambled on targeting one powerful voting bloc, (some pollsters thought this would alienate too many people) suggests Harvard’s professor Stephen Greyse (Fottrell 2016).   Clinton’s target audience was far broader, reaching out to the middle-class and “left-out” voters and black and Latino ‘left-out’ voters (many of whom had not yet a slice of the American pie). A month before the elections Trump had 57k transactors (contributors) of whom 68% were male and 32% were female, compared to Clinton who had 914k transactors of whom 36% were male and 64%  were female. Far more variables were eventually used to segment the market into dozens of target segments. In fact, a small English company who had also worked on the Brexit ‘Leave’ campaign for UKIP, worked for Trump and divided the US population into 32 personality types, and focused on just 17 states (see part 3).

Why – do Trump’s potential voters vote (what are their needs)?

Many people wanted change. Many others were frustrated and maybe even angry about their lives. Some have fears rather than hope. Is it possible that Trump’s upbeat’ #MakeAmericaGreatAgain or #MAGA hashtag played into the unconscious fears that if you don’t vote for Trump, America will get worse ie whatever is bad about America will become far worse? See the word-cloud graphics (in the final, ‘Control’ section) which demonstrates how Trump repeated these messages.

What the elite missed was the sources of the anger & resentment that has lead to the populist upheavals in the US & Britain & many other parts of the world (Harvard’s Professor Michael Sandel 2017).

Why were voters angry? What the elite missed was the sources of the anger & resentment that has lead to the populist upheavals in the US & Britain & many other parts of the world. (They) assumed it’s anger against immigration and trade and at the heart of that is jobs. But it’s also about even bigger things., about the loss of community, disempowerment, & social esteem (a sense that the work that ordinary people do is no longer honoured & recognised (& rewarded).’ Sandel 2017)

How – do Trump’s potential voters decide (how do they process information)?

Shorter attention spans. Research from Harvard revealed that attention spans for the first ever telivised political debate between JFK and Nixon back in 1960, was only 42 seconds (the maximum time to get a serious political message across). This fell to just 5 seconds in 2008 and even less since in 2012. There are many other variables involved here also, but, short attention spans is significant and perhaps gives a clue why Britain voted marginally for Brexit (short anti-EU messages had far more impact than long economic pro EU messages). 

Voter Personality Analysis – Cambridge Analytica & Trump

UK Company Cambridge Analytica analysed facebook data of millions of adult Americans, so that they could categorise personality types and then subsequently send them tailored messages that reflect their specific needs. ‘The company’s former boss, Alexander Nix, claimed, before the election, to have predicted the Big 5 score (personality analysis) of every adult in America. On Facebook, hundreds of ads were posted everyday targeted at specific personality types tailored towards people’s innermost fears, needs and emotions.’ BBC News 2018

It used an algorithm that analyses what people like (and don’t like ) on facebook to predict your personality. With just 10 likes it can predict what kind of person your are, better than your colleagues can. With 300 likes analysed, it knows your personality more accurately than your spouse does.

For more frightening insights into how this analytic tools and subsequent tailor-made ads were targeted precisely to each personality type, see The Dark Arts Of Marketing – Breaking Down Society to Create a New Culture – Using Data & IRD when a Cambridge Analytica whistleblower reveals the dark marketing techniques that were employed.

Major Market Trend – A Gap In The Market

We live in a post truth-era. ‘Dishonesty in politics is nothing new; but the manner in which some politicians now lie, and the havoc they may wreak by doing so, are worrying’ says the  Economist magazine (2016). The worrying phrase ‘post-truth’ was even named Word Of The Year by Oxford Dictionaries (Flood 2016). Defined by the dictionary as an adjective “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief”. The spike in usage, it said, is “in the context of the EU referendum in the United Kingdom and the presidential election in the United States”.

This is compounded by the moral vacuum which opens the gates for extremist politicians. Here is Harvard Professor Michael Sandel’s chilling observation: “… in the face of pluralism  and for the sake of toleration … to insist on a non-judgemental, value-free politics .. that creates a moral vacuum , a void, that will invariably will be filled  by narrow, intolerant moralisms.” Sandel (2017)

Competitor Analysis

During the Republican nomination race, Trump saw a right-wing gap and went for it. He also analysed the political establishment through the eyes of disenchanted voters. Trump became the Republican candidate for the presidential election. Next, he analysed his opposition, the Democrats’, Hilary Clinton. When he found a perceived weakness that resonated with his voters (see the Control section in part 2) he went for it. President Obama had unprecedented success in targeting, organizing and motivating voters, we imagine Trump’s team studied this blog post How Obama Became America’s First Black President to understand his competitor’s strategy and tactics.

This image went viral during the 2008 campaign with the caption: ‘This seat is taken’

Current Performance

With the election just a month away, donations raised by October 2016: Clinton had $298m from 914,000 transactors (donors) and Trump had just $50.1m from 57,000 donors (Cortana et al).

Opinion polls favoured Clinton.

Objectives

Originally to win the Republican Nomination and then, win the presidential election (after that we just don’t know).

Strategy

Old Strategy

Trump initially raised his own profile by making headline-grabbing statements, often by calling in to television shows, supplemented by a rally once or twice a week to provide the appearance of a traditional campaign (Bertoni 2016).

New Strategy

Trump’s crystal clear positioning as the ‘controversial (non-establishment) ordinary guy’  was supported by data driven highly targeted tailored messages on facebook & twitter to “left-behind”  white working-class men (and women), combined with sentiment manipulation, machine learning, constant beta culture and, almost instant, reactions to audience mood swings

Trump’s son in law, Jared Kushner, took over the campaign, created this new strategy and, amongst other things,  set up a secret data operation-like a Silicon Valley startup. ‘Kushner eventually tipped the states that swung the election. And he did so in a manner that will change the way future elections will be won and lost.’ (Bertoni 2016).

Positioning

Trump positioned himself as a non-establishment guy. An ‘outsider’ – a ‘non-political establishment guy’.   He simultaneously positioned Clinton as an establishment person. An ‘insider’ (a politician linked to Obama’s policies) (Kanski 2016). Trump played the confrontational card which helped him to establish authenticity amongst frustrated voters. So he became a ‘controversial (non-establishment) ordinary guy’.

Meanwhile, Trump positioned Clinton as an untrustworthy ‘insider’ and threatened to take her to court after the election. Clinton’s authenticity was challenged by high-lighting the fact that ‘she seemed to say one thing in her speeches and another behind the scenes, illustrated in her emails leaked by Wikileaks and “basket of deplorables” comments (Kanski 2016). The CIA revelations days before the vote appeared to attack Clinton’s authenticity. Or was all this information fed by the Russians? There’s definitely a movie in this story.

‘controversial (non-establishment) ordinary guy’    v     untrustworthy ‘insider’ establishment lady

Was it like this?

a possible perceptual map

Apart from Clinton’s followers, one wonders whether the average American could relate to Clinton as easily as they could to Trump (or Obama in the previous two elections).

The ‘Ordinary (non-establishment) Guy’ Created Authenticity

While Trump followers believed Trump had authenticity as he, rightly or wrongly, ‘says it like it is’.  The difference in authenticity, according to Kanski, was simply that ‘People can relate to bankruptcies, to locker room talk, to tough talk on terrorism, and that was the difference. Whilst Trump might be a billionaire, but he’s been bankrupt, uses locker-room talk i.e. his life experiences somehow seemed to resonate more with the average undecided voter.’  

ordinary people

white working class

blue collar workers

Targeting

Trump stayed focused on the “left-behind” voters, specifically white working-class men (and women). As mentioned earlier, this was deemed risky (targeting one powerful voting bloc).  Clinton’s target audience, on the other hand, was far broader, reaching out to the middle-class and black and Latino ‘left-out’ voters (many of whom had not yet a slice of the American pie). Trump’s relentless use of data continually sharpened his targeting of those battleground states (the ‘swing states’, that over recent elections have gone both ways). They are the key to winning the election. In recent elections Florida and Ohio (3rd and 7th largest states, with 29 and 18 electoral votes respectively) have been swinging back and forth between the parties.

Data-driven Decision Making

Within three weeks, in a nondescript building outside San Antonio, Kushner had built what would become a 100-person data hub designed to make more informed decisions (which leveraged the magic marketing formula – see part 2) across a selection of decision points regarding:

• messages (topics of speeches)
• targeting
• travelling / rally locations
• fundraising

Kushner built a custom geo-location tool that plotted the location density of about 20 voter types over a live Google Maps interface

Trump combined his crystal clear ‘non-establishment’ positioning, data-driven targeting, with agile use of the Magic Marketing Formula to win. His subsequent tactics were driven by the over-riding strategy. Part 2 explores the second half of SOSTAC® – Tactics (including the Magic Marketing Formula), Action and Control.

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See How Trump Won (part 2) – using The Magic Marketing Formula – a SOSTAC® Analysis and later  – How Big data was used to win the election (part 3).

You might also enjoy:How Obama Became America’s First Black President

You might not enjoy, but perhaps need to see this video on behavioural analytics and precision targeting:
The Dark Arts Of Marketing – Breaking Down Society to Create a New Culture – Using Data & IRD

How SOSTAC® Works – a 4 minute video by PR Smith

The SOSTAC® Guide to your Perfect Digital Marketing Plan 

For more on SOSTAC® Planning System and Certified SOSTAC® Planners see www.PRSmith.org/SOSTAC

The new SOSTAC (r) Guide for Digital Marketers

Become a SOSTAC® Certified Planner  visit www.SOSTAC.org

Sources:

Bertoni, S. (2016)   How Jared Kushner Won Trump The White House , Forbes December 20

Economist (2016) The post-truth world: Yes, I’d lie to you, 10 Sep 

Flood, A. (2016) ‘Post-truth’ named word of the year by Oxford Dictionaries, The Guardian, 15 Nov.

Kanski, A. (2016) Change and authenticity: The messages that won over American voters, PR Week 09 Nov.

Sandel, M. (2017) ‘ Why The Democrats are so out of touch with the People‘, World Economic Forum, Davos 2017

The post How Trump Won (a SOSTAC Analysis) – Part 1 appeared first on PR Smith Marketing.