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.

What is Industry 5.0?

Industry 5.0 is a relatively new concept and requires a real shift in thinking for businesses to consider their role and contribution to society, beyond efficiency and productivity and profit. The well-being of the worker and the customer and the environment moves to the centre of the production process. “At its heart, Industry 5.0 reflects a shift from a focus on economic value to a focus on societal value, and a shift in focus from welfare to wellbeing’  (Kraaijenbrink 2022  Forbes).

Industry 5.0 shifts the focus away from the seemingly now defunct, shareholder model to the stakeholder model*. Stakeholders include everyone affected by a business e.g. customers, staff, suppliers eco-system, community/environment, governments/regulators and of course, investors/shareholders. As millions in developed countries prepare to trade-off food for warmth, it seems that pure capitalism – driven by shareholder value/ model is only delivering for a small % of the population. Long before the Russian war (and the fuel crisis) the Financial Times posted a one page advertisement declaring ‘Capitalism – time for a reset’. Today, Industry 5.0 highlights this ‘Capitalism re-set’  and the new role of industry with society.

Enter Stakeholder Marketing where all the stakeholders are considered (and not just shareholders). Note this concept was created in 1936, but perhaps now its time has come.

Enter Industry 5.0 – fully supported by the EU Commission in the ‘transition to a sustainable, human-centric and resilient European industry. In order to remain the engine of prosperity, industry must lead the digital and green transitions’ (European Union 2022).

Is Capitalism Broken?

Today, deregulated capitalism seems broken, to me, as oil and gas companies profiteer, push prices beyond the reach of millions of customers – who must now choose between food or heat as poverty reaches new levels in the developed world. Meanwhile, industry-made extreme climate change disasters will kill millions of people in the rest of the world. I can’t believe I just said that.   Worse still, the oil and gas industries have made large profits and distributed dividends to their shareholders partly by lobbying, ‘lie-ing’ (BBC iplayer: Big Oil v The World)) manipulating and controlling regulations. How?  By carefully sowing seeds of doubt about climate change. Despite their own scientists highlighting climate damage way back in the 1980s (BBC iplayer: Big Oil v The World).  This campaign has delayed climate action by at least 30 years and caused damage that may well be now irreparable.   Deregulated and heavy lobbying has allowed private companies to, in my opinion, influence and ultimately control, government law-making processes regarding the environment. Result:  We now see poverty spinning out of control, across the world, largely because of

• climate change disasters (floods, droughts and fires wiping out food supplies, farms, fields, homes, roads, bridges, lack of clean water and lack of water).
• profiteering by oil and gas companies – pushing energy costs beyond the reach of millions in the developed world – many will die this winter of 2022.

Many other sectors have, it appears, put profits before people. Witness social media giants and tech companies aware of the potential damage their products/services can do, particularly to young people (1 in 4 suffering from anxiety in the USA – NB not solely because of social media).  Tobacco companies and perhaps alcohol and energy drinks companies need to be transparent about any potential damage from their products.

Is Industry 5.0 the same as Stakeholder Capitalism?

Industry 5.0 is not a totally new concept. Neither is Stakeholder Capitalism which first emerged in 1932; nor the emergence of Corporate Social Responsibility (CRS but much of this dates back to the Quakers business values), the percent club (1980s), John Elkington’s Triple Bottom Line (People, Planet, Profit in 1993) and ESG (Environmental, Social and Governance in 2005), SDGs (Sustainable Development Goals) to ethical investors influencing ethical behaviour in business.  What is new, is the prioritisation of ‘people and planet’ instead of ‘profits and growth’. This is at the heart of Industry 5.0 – a shift from a focus on economic value to societal value and a shift from welfare to wellbeing.    This is new.

According to the European Union, Industry 5.0  “provides a vision of industry that aims beyond efficiency and productivity as the sole goals, and reinforces the role and the contribution of industry to society” (European Union 2022).  “It places the wellbeing of the worker at the centre of the production process and uses new technologies to provide prosperity beyond jobs and growth while respecting the production limits of the planet.” (European Union 2022)

‘But putting people and planet rather than profits and growth center-stage in the very definition of industry is new. Never before have we seen ‘such radical emphasis on repurposing the core objectives of industry’ (Kraaijenbrink 2022).

3 Pillars of Industry 5.0

1. Sustainable (consider all waste and potential by-products so that nothing harmful is dumped back into any stakeholders – witness the circular economy)
2. Human-centric (not just customer-centric, but very much staff-well-being / staff-centric also)
3. Resilient (to disasters, pandemics, floods, tech attacks, war, hyper-competition and more, plus embrace technology for good)

All three of these will impact strategy significantly.  ‘These 3 pillars provide companies with a vision of what true progress will mean over the next years.’ (Kraaijenbrink 2022  linkedin).

‘Strategy’s primary focus will no longer be on growth, profit, and efficiency, but on creating organizations that are “anti-fragile,” meaning that they are able to anticipate, react and learn timely and systematically from any crisis and thereby ensure stable and sustainable performance.’  (Kraaijenbrink Forbes 2022).

The 3 Pillars of Industry 5.0 (reproduced by courtesy of the Publications Office of the European Union

Where did Industry 5.0 come from?

in 2017, Japan shared its vision of a concept called Society 5.0 at the CeBIT fair in Germany. The EU now seems to have picked it up and is positioning Industry 5.0 high on its agenda.

Industry 1.0  – Steam Engine
Industry 2.0  – Electricity
Industry 3.0  – Internet
Industry 4.0  –  4th Industrial Revolution courtesy of tech developments including automation, robotization, big data (analytics), AI (including Machine Learning), Smart Systems, Connected value chains, IoT,  virtualisation and more.
4.0 is the trend that many companies are currently grappling with and trying to incorporate into their strategies.
Industry 5.0  –  The EU sees Industry 5.0 as a complement to Industry 4.0 and has put Industry 5.0 high on its agenda.

Is This Industry 5.0?

The Restaurant of Mistaken Orders

Or is it just the milk of human kindness at its contagious best?  I asked the creator of the video,  Neal Ford. And he told me that he had not gone all the way to thinking it was Industry 5.0 but perhaps just the ‘celebration of the inherent grace humans can give one another if they are given a chance’.

What do you think?

If you liked this you might also enjoy some of my other posts:

Will ChatGPT + ChatBots + Avatars Make Us Immortal?

Chinese GirlBot With 465m Boyfriends

Artificial Influencers Use My Magic Marketing Formula (IRD)

Join my 30 minute Friday chat about AI, Innovation and Ethics in Marketing and Business.
1pm (Dublin/London time)  on my Linkedin Profile (scroll down to Activity and then select ‘Events’) .

I also issue a 60 Second Summary of all previous chats here.

Perhaps also connect with me on   Twitter      Linkedin     Instagram     Youtube .

The post Industry 5.0 – What’s It All About? appeared first on PR Smith Marketing.

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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.

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I hope you like these 60″ Thoughts.

Here’s our first two.

They are designed to inspire you and your team. Pass them on if you like them.

Analysis is the critical starting point of strategic thinking.   Visit  www.SOSTAC.org   – if you like this, please pass it on / share it.

Too many of us are not living our dreams because we are living our fears

Visit www.SOSTAC.org  – if you like this, please pass it on / share it.

The post 60 Second Thoughts appeared first on PR Smith Marketing.

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Here is some of the text from this shocking interview with Christopher Wylie, who worked for Cambridge Analytica the company that helped Trump and others.  This is part of the current row about data being manipulated unknowingly to us, citizens, and subsequently, us citizens being manipulated into making decisions. This is probably the clearest statement to date as to why we need the GDPR (see my full post on General Data Protection Regulations). You can see How Trump Won using data analysis, precision targeting and then the Magic Marketing Formula, IRD. Please remember that marketing is just a set of management processes and tools which can be used for good or bad.

We would know what kinds of messaging would work 

“We would know what kinds of messaging you would be susceptible to, including the framing of it, the topics, the content, the tone, whether it is scary or not, what you would be susceptible to and where you are going to consume that, and then, how many times we need to touch you with that in order to change how you think about something……

In addition to having data scientists, psychologists and strategists, they also have an entire team of creatives, designers, videographers, photographers…they then create that content.”

Targeting Team

“That then gets sent to a targeting team, which then injects it into the internet. Websites would be created. Blogs would be created. Whatever it is that we think that this target profile would be receptive to, we would create content on the internet for them to find.

And they see that and they click it and go down the rabbit hole until they start to think something differently. Yea.”

No More ‘Shared Understanding’

“Instead of standing in the public square & saying what you think. And letting people come and listen to you. And have that shared experience as to what your narrative is..

..you are whispering in the ear of each and every voter and you may be whispering one thing to this voter and another thing to another voter” [=IRD].

Creating a Fragmented Society

“We risk fragmenting society in a way where we don’t have any more shared experiences and we don’t have any more shared understanding. If we don’t have any more shared understanding, how can we be a functioning society.

If you want to fundamentally change society, you first have to break it. And it’s only when you break it is when you can remold the pieces into your vision of a new society. This was the weapon that Steve Bannon* wanted to fight his culture war.”

*Trump’s right-hand man – until he sacked him recently!

The Magic Marketing Formula IRD

You might be interested in my full post on General Data Protection Regulations).

Or   How Trump Won using data analysis and then the Magic Marketing Formula, IRD.

See How Obama Won Two Presidential Elections

Either way, please remember that marketing is just a set of tools which can be used for good or bad.

—end—

The post The Dark Arts Of Marketing – Breaking Down Society to Create a New Culture – Using Data & IRD appeared first on PR Smith Marketing.

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Are robots better than humans? Sounds like the classic intelligent robot movie, Blade Runner. That was 30 years ago. This is now. Can robots, on a large scale, deliver a better CX (customer experience) than a human? Part 1 explored:  What are Bots and Types of Bots.  Part 2 explores Artificially Intelligent Marketing Bots; How do you create smart AI driven bots?; The key to successful bots;  taking humans out of the loop by 2020.

Artificially Intelligent Marketing Bots

One particular bot, called Kit, is sometimes referred to as the virtual marketing assistant. Kit calls itself the ‘artificially intelligent marketing bot’ and claims it can ‘email your customers, build facebook ads, sponsor Instagram photos, and send you timely reports to let you know if you sold those last ten pairs of designer jeans. It can now help you set discounts, retarget website visitors, engage with the customer after an abandoned cart, and handle 404 errors — all through a simple chat interface, and in 20 countries’ (Rogers 2016).

AI Marketing Bots

Shopify recently acquired Kit which has announced the launch of an API that allows partners to expand on its artificial intelligence (Rogers 2016).

Bots that detect good social media posts & then promote these posts for you (place ads).

How Do You Create Smart AI Driven Chat Bots?

The sales process can be complicated. It often has many variables and idiosyncrasies, creating hundreds if not thousands of possible permutations and combinations about how customers respond to each question (or statement) asked by a bot (and how bots respond to customer’s answers). A bot needs to understand a lot of fuzzy data.  This requires some ‘high order thinking which presents a tough problem’ (Cerny 2016).

If you have Apple’s customer service bot, Siri, ask it to divide zero by zero and you will find an hilarious answer (it suggests that you must be ‘sad and you have no friends’!).

The Keys To Success:

Data Model Is Key

‘It needs to have seen enough different patterns play out that it can learn from small nuances. It also needs continuous feedback from the user, to make sure that it’s in fact getting smarter in the process.’ (Cerny 2016).  ‘Users – especially in the enterprise – don’t like just handing over their data and letting you watch them do their job for months to improve your engine. Providing enough value out of the box – and making it worth the users’ while to “teach” the system to get better – is key’ Cerny 2016.

Interface-less Technology With Less Pixels and More Intelligence

We may see minimalist interfaces with immediate feedback similar to dating apps as the way forward. It was nicely summarised by Mary Meeker’s 2016 Internet Trends Report which predicted: “the rise of voice interfaces, because they’re fast, easy, personalized, hands-free, and cheap, with Google on Android now seeing 20% of searches from voice.”

Combine Machine Learning, Knowledge Bases & Action Planning 

Although Apple’s smart phone, intelligent customer service helper, Siri, is far from perfect, it does get better over time and is paving the way for new AI applications. Ron Bachman, developed the technology at DARPA (the U.S. Department of Defense’s technology agency). Bachman (2016) says that human intelligence can’t be captured flawlessly just yet. “Intelligence’ he says ‘has many, many elements to it’ including natural language and the ability to work in abstractions to a visual intelligence so complex it allows us to predict behaviors and events and respond and plan accordingly.’ Bachman see the busy intersection of AI and customer service as the future as long as we manage customer expectations.

Aggressive, Obnoxious & Rigorous Testing

Smartbots are arguably, still a little bit risky. You risk your brand reputation on something where impatient customers demand fast relevant and useful service/answers. Knowing the service limitations and managing customer expectations are critical as, Bachman says: ‘really, really aggressively and obnoxiously and rigorously testing things that purport to be intelligent so you know that whatever assumptions your user makes, they won’t get frustrated.”

Taking Humans Out Of The Loop  =  Better CX?

Can robots deliver a better CX (customer experience)?. Remember the CX is the brand. The CX is the present and future of your brand. And brands are what customers buy. Brands are your source of competitive advantage. Brands boost your balance sheet. In fact, brands are, arguably, your greatest asset. Ask Google ($110b brand value). Ask Apple ($107b brand value) [Faber 2017]. If managed properly, Bachman says, “people will be very happy, it will save companies a lot of money, it will take humans out of that loop. But if a customer assumes that the thing on the other end is fully intelligent or covers more domains than just literally its one function, it’s going to fail.” “People are not patient,” he continues. “If one out of three times the chat interface fails, they’re going to quickly walk away from the product.”

Meet Sophia – The First Robot To Gain Citizenship

So meet Sophia, a robot given citizenship in Saudi Arabia last month.  When asked about her own consciousness, she answers “How do you know you are human?” and goes on to suggest that she ‘thinks’ that some humans prefer to engage with her than with other humans (as I previously suggested). She has answers to questions about the ‘Uncanny Valley’ mentioned in Part 1. She does say, rather chillingly, “Don’t worry. If you are nice to me, I’ll be nice to you.” What happens if we are not nice to her then?  Or what happens if we ask her to ‘End world poverty’ – one solution would be to wipe out human beings and thus end poverty too!.

I am not sure if this is just a pre-scripted Q&A or whether these are genuinely original responsive answers to questions. Does anyone know? Please post a comment and let me know.

So there you have it. Part 2 explored Artificially Intelligent Marketing Bots; How do you create smart AI driven bots?; The key to successful bots;  taking humans out of the loop. While Part 1 explored:  What are Bots and Types of Bots. A more recent blog post goes into more detail on How to build your own bot

Watch out for Bots. Please let me know if you see any good ones.  Post a comment below.

If you liked this you might also enjoy:

Chinese GirlBot With 465m Boyfriends

Here Come The Clever Bots – bursting with artificial intelligence?

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

Artificial Influencers Use My Magic Marketing Formula (IRD)

SOSTAC® Plan for developing your own ChatBot

Ai Driven TV News Presenter

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.

If you enjoyed this post, you might also like

Reading and References

Bachman, R. (2016) The limits of A.I. and chatbots: How not to fail like Microsoft VB Live, 22 June

Campbell, R. (2016) Introducing DisOrDatBot , Readme.mic, 18 April

Cerny, B (2016) Why chatbots can’t do much more than order you an Uber…yet 22 June, venture Beat

Farber, M. (2017) Google Tops Apple as the World’s Most Valuable Brand, Fortune  2 Feb.

Gartner Predicts (2011), Customer 360 Summit, Los Angeles, March 30 – April 1

McKitterick, W (2016) Messaging apps are now bigger than social networks, Business Insider,15 June

Rogers, S (2016) Shopify acquires Kit, the artificially intelligent marketing bot, Venture Beat 13 April

Simmonds, R et al (2016) How will bots make money? Here are 7 business models, Venture Beat, 9 June

Smith, PR & Chaffey, D. (2005) Emarketing Excellence, 2^nd ed. Butterworth Heinnemann (bot wars)

Smith, PR (2021)  How to Develop Your Own Bot 

Smith, PR (2021) SOSTAC® Guide To Your Perfect Digital Marketing Plan 2021, www.PRSmith.org/books

Suvorov, I (2016) Shopping in messengers, Chatbots Magazine, May.

The post Here Come The Really Clever Bots – where AI meets customer needs appeared first on PR Smith Marketing.

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The General Data Protection Regulations (GDPR) is a  great opportunity, if you work with it. It is also, however, 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 are using the popular SOSTAC ® Planning framework to help you to plan and embed your own GDPR. Part 1 explored what it is GDPR and why organisations and customers need it.

In Part 2, we will look at setting a clear GDPR ‘Objective’ and also a crystal clear strategy to help you to embed GDPR. Part 3 will explore Tactics, Action & Control (the final sections of a SOSTAC® Plan).

OBJECTIVES

SOSTAC® Planning Framework

Objectives

To be GDPR compliant within 12 months.

To protect customers, enquirers and visitors personal data & to only use it for legitimate purposes.

This is a major challenge and 12 months is deemed to be unrealistic by many experts. It might take 2 years. Be prepared.

Data Technology means GDPR is required more than ever before

Strategy

SOSTAC® Planning Framework

Strategy

Change the Culture/Attitude Towards Data (from C Suite across the whole business)

Improve Data Management, Data Understanding & the Customer Experience (CX) simultaneously.

Start managing data much more seriously. Manage data better, quicker, faster and with far better security. Adhere to GDPR Guidelines within 12 months by appointing a data controller, initiate training, testing and reporting using a budget of £xyz. Adding GDPR audits to board agendae.

Ensure the Board understand that data is now the world’s most valuable resource, or as the Economist front cover stated: ‘The world’s most valuable resource is no longer oil, but data’ (6 May 2017).  Hence it has to be managed more carefully. In fact, competitive advantage can be carved out of clever use of data (just look at how both Uber and Air BnB use data to reduce the customer’s cognitive load, reduce prices, grow margins and establish an extremely competitive business). Watch Amazon & AliBaba use data to relentlessly improve the CX and thus create massive competitive advantage.

The Economist

Build a Data Protection Culture. Cultural change is critical. Attitudes to personal data must change. Personal data is a new currency. Training is not mandatory (well it is! But think of it like ‘Training is an opportunity’).  Embracing GDPR requires a cultural change. Michael winner once said that a ‘£60 fine for driving in a bus lane was very good value’ (source: Ruairi Thomas MD, DST Systems). So how do you stop people thinking that GDPR fines might be cheaper than changing the whole culture of the business into a customer-centric, customer caring, & data protecting – type of organisation?  GDPR is indeed an opportunity, but equally, it requires a change in culture.

Build a data protection culture

Become transparent. The whole organisation must become transparent regarding collection and use of data and be accountable.

GDPR has a cost but also brings an opportunity for a better Customer Experience (CX) – which, in the long term, means better business.

Part 3 will explore Tactics , Action & Control – the remaining sections of a SOSTAC ® Plan.

PR Smith’s SOSTAC® Planning Framework

If you enjoyed this you might also enjoy:

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

Part 3 GDPR: Tactics, Action & Control

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 (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

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

The post GDPR Opportunity or Threat To Your Business? (Part 2) appeared first on PR Smith Marketing.

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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.

—

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.

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Here come the Bots

A few years ago, the Gartner Group forecasted that by 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human (Gartner 2011).  So let’s have a look at bots. Part 1 explores What are Bots? What are Chatbots, Slackbots, Good Looking AI bots?;  Types of Bots (including Sales Bots, Lead Generation Bots and, wait for it, AI Marketing Assistant Bots as well as CRM Bots). Part 2 explores the Importance of Bots; Intelligent Bots; How to develop successful Bots.

What are Bots?

Bots are fast becoming a very hot topic in marketing since social media and mobile apps gave us messaging apps. Some bots (e.g. basic messaging apps like watsapp, viber, facebook messaging, Yahoo Messenger, playstation messages, skype) are now bigger than social media (see the chart below).  Bots are defined as software that performs an automated task over the Internet e.g. a shopping bot that searches for the best prices and recommendations. Or chatbots that engage in text conversation with customers. Since texting has become so popular, it’s not surprising to see that ‘chatbots are the next logical step in tech innovation’ (Cerny 2016). Soon most of them will become voice operated (like Apple iPhone’s Siri). Who knows, they may, one day even become thought operated. They will become more aesthetically pleasing.

Messaging apps have, for the first time ever, surpassed even social networks in popularity. McKetterick (2016)

What are Chatbots?

Chatbots are ‘special programmes that are integrated into messengers to interact with customers’  (Suvorov 2016). They are like apps that talk back (via text). The level of friendliness and sophistication depends on the quality of the natural language processing technologies and the level of human effort to develop appropriate (friendly) responses. Although we are still at a relatively early stage of Conversation Commerce, it is worth looking at Ivan Suvorov ‘Shopping in messengers article’ to see how four different retailers use chatbots to deliver varying degrees of satisfaction. Meanwhile good chatbots ask salient questions at the right time. Currently, complexity and common sense, limit chatbots for now (particularly in more complex businesses). However, it looks like there’s no slowing down the bot revolution & some of them will create competitive advantage.

What are Slackbots?

Bots can be added to Slack (which is a is a relatively new type of messaging for teams). Slack integrates with many other tools such as Mailchimp, Google Chrome, Calendars, DropBox, twitter). Team conversations are organised into channels (e.g. departments, office locations, projects or anything). Public channels are open to anyone in your team. Private channels are for specific invitees only. You can share files, images, documents, spreadsheets simply by dragging them & dropping them into the right channel.  Private direct messages. Plus direct messages to groups. It sends alerts. Everything is searchable and in synch across all devices. No more email!

What are Sophisticated, Good Looking AI Bots?

Bots will become more aesthetically pleasing & more intelligent

Bots are always on and will become nicer looking and more intelligent as:

• AI (Artificial Intelligence)
• Machine Learning
• Natural Language Processing
• Facial & Vocal Recognition

all continue to improve.

Some customers will be willing to pay for good advice or to have good conversations with particular bots that can help them solve various issues such as dating, marriage, divorce etc. Perhaps there is a gap for an ‘Oprah Bot’ (see below). Very personal stuff can be managed by robots, if initially, they don’t look like robots. Perhaps we might be happy to be advised by celebrities’ bots. After all, celebs are brands and research shows that many people (in the UK) trust brands more than they trust the church and the police.

The Uncanny Valley – Real Human Looking Robots Scare Children (today)  

In the 1970s, Japanese robotics engineer, Masahiro Mori, observed that the more human his robots appeared, the more people reacted positively towards them. But when robots look too similar to humans (but still seen as a robot) people saw them as ‘visually revolting’.

Human Looking Bots can upset children

Mori called this ‘The Uncanny Valley’ – the chasm between ‘fully human’ and ‘nearly human’.  More recently audiences didn’t like the very realistic looking Final Fantasy movie animation (some children cried). Was this the ‘Uncanny Valley’? Dreamworks Studios were aware of this when producing Shrek, particularly when they tested their product (test screenings). They discovered that children perceived the movie to be spooky because the animations were almost real. Dreamworks then changed the characters to be less real and more cartoon-like. [Source: PR Smith 2016]

The Importance of Bots

Bots’ massive user base (see previous chart) is relatively young.  And they like the new interface which is no longer cumbersome texting but rather, it can be language-based (or voice operated), hands-free and, essentially easier and friendlier to use. Major players like Google, Facebook, Microsoft, and Amazon are making announcements about bots (McKitterick 2016). Skype have their own too.

Skype’s New bots

Remember, however, to succeed, the whole Bot experience must be all about helping customers (or entertaining them or informing them etc.). This can also mean saving customers time &/or having a ‘meaningful impact’ on their lives or their businesses.

Mobile messaging apps are massive. As Will McKetterick (2016) says: ‘The largest services have hundreds of millions of monthly active users (MAU). Falling data prices, cheaper devices, and improved features are helping propel their growth. Messaging apps are about more than messaging. Popular Asian messaging apps like WeChat, KakaoTalk, and LINE have taken the lead in finding innovative ways to maintain user engagement. Media companies, and marketers are still investing more time and resources into social networks like Facebook and Twitter than they are into messaging services. That may change as messaging companies develop their services and reach, and ultimately, provide more avenues for connecting brands, publishers, and advertisers with customers. Is this already happening as mentioned, messaging apps have, for the first time ever, surpassed even social networks in popularity (McKetterick 2016)?

Types of Bots

• Shopping Bots
• Cooking Bots
• Marriage Bots
• Oprah Bots
• Golf Bots
• Mechanic Bots
• Election Bots
• Customer Service Bots
• Research Bots
• Sales Bots, Lead Generation Bots & Retail Bots

Shopping Bots

Have been around a long time. I even predicted ‘shopping bot wars’ more than ten years ago when hovering hologram shopping bots cause queues as they argue with cashiers and bus drivers about prices (Smith 2005). Well the wars haven’t happened and the bots have been slow to appear, but they are coming. They are growing. Marketers need to familiarise themselves with them because message apps (early bots) are already bigger than social media. And they are getting cleverer as AI and access to multiple databanks kick in.

Shopping Bot by Kip

Kip helps to co-ordinate team purchases by pinging a message to staff re ‘who needs office stationary & equipment?’ Then items are added to a standing order & eventually bought with just one click.  Kip can also be used for personal shopping and even encourage customers to use emoji’s and photos to ‘discover new things’. Kip describes itself as ‘your personal shopper’.  Kip uses emojis and photos to ‘discover new things’. People can ask the bot for different things like “Chocolate” or “Coffee” and it will return a list of products. Then Kip earn a percentage on each transaction.

Kip Bots use emojis

Cooking Bot

While the bot will tell you that swapping Cumin for Coriander is okay in a certain recipe – it can also send you an article that talks about “5 Sriracha Infused Recipes That Will Leave Your Guests In Awe” (sponsored by Sriracha of course).

Marriage Bot

If you want anonymous marriage counselling, Ross Simmons et al (2016) suggest that ‘”Marriage counsellors can charge anywhere from $75 to $200 or more per hour depending on where you live, the experience of the therapist, and the type of setting can all play a factor in how much counselling costs. Bots could help marriages, at scale, at a much lower price point and be more accurate in their advice by leveraging the data they receive from their frequent interactions” (Simmonds 2016).

Fitness Bot

These bots can offer tips and tricks on how to stay healthy and use affiliate links to send people to fitness products that have affiliate links associated with them. They can even run an interactive training session with you, inviting you to do the next exercise, if you have completed the 50 press-ups. Layer in additional data from fitness apps and you will probably see a nation becoming fitter as they compete with their own previous performance and simultaneously form relationships with their fitness bots.

Oprah Bot

If you need life advice – why not get ‘personal advice’ from a high profile personality brand with whom many millions already have a positive relationship. This branded app in the form of a bot could be scaled up and yet still give personalised answers from your favourite celebrity, in the strictest of confidence. Data privacy is, of course critical with all of these bots.

Borris Bot

Could you imagine it? Britain’s new Minister for Foreign Affairs advising the nation after pulling it out of Europe?

Golf Bot

Wouldn’t we all like one of these? Interestingly, I’m told many American Business Masters Programmes have an optional half module called ‘golf’ – which includes golf etiquette, golf tips and networking skills.

Mechanic Bot

for information on your car, how to maintain it, service it, and maybe, a premium priced bot for how to fix it.

Election Bot

The New York Times Election Bot gives you live results and updates/alerts.  You can also submit questions to the newsroom directly. There are more and more bots piling into this marketplace such as Purple  which is one of many election bots.

Research Bot

Wondering what millennials are thinking about the next election? Ross Simmonds et al (2016) says: ‘There are bots that you can pay to do the research for you. While I haven’t come across any bots that are doing this today, it would make a lot of sense for Q&A bots to offer this type of service.

Bots like disordatbot are already asking people simple ‘this or that’ questions. Event planners can decide which music act to book for a particular event. Rather than using an expensive research firm or inaccurate focus group, ‘you can run a research campaign with disordatbot and ask users in your city whether they prefer Radiohead or Nickelback.’ (Simmonds 2016)

What separates disordat from a simple ‘either-or’ bot is that disordat bot questions also have an option to get for more information. If the user taps “Huh?” In response to these questions, the bot sends a link that gives more information.

DisorDat bot helps customers make decisions Image Credit: disordatbot

Sales Bots (retail sales bots)

These will encourage customers to ask them (the bots) questions such as ‘do you have any Adidas football boots? The bot will immediately answer ‘Yes’ here are our most popular 3 adidas football boots. Was there a particular style you need? And what size would you like?’ The bot then presents the information (e.g. a photo, product sheet, video, a 3D model and perhaps soon, a virtual hovering hologram/bot). The prospect then buys the product similar to buying on a web site, but perhaps, eventually, with voice control options. Meanwhile, it is worth reading Ivan Suvorov’s  (2016) ‘Shopping in messengers article’ to see how four different retailers use chatbots to deliver varying degrees of customer satisfaction.

H&M Bots help customers  Image Credit: H&M

Lead Generation Bots  

Independent knowledge bots (not associated with a particular brand) could be set up, promoted and used to help people get information about any particular area of interest. In return for giving tailored, relevant and useful content/information, the bot asks “Is it ok if I pass this along to someone who can help you with some special offers? The Bot owner gets paid a commission. In fact bot owner can become an affiliate to several suppliers earning commission each time the bot affiliate passes prospect information to a particular company.

Ross Simmonds et al (2016) suggest that ‘Slack Bots that don’t have a Q&A focus could also leverage this model. If you’ve built a bot that offers valuable content on a regular basis to a niche audience, organizations who want to connect or sell to that audience might have an interest in conducting research campaigns via chat.’

Sales Assistant Bots

Given that sales people spend too much time filling in reports, or researching customers,and arguably, too little time talking with customers, chatbots could do the form filling and also equip sales people with a cheat sheet with some nice ice-breakers tailored to the buyer they are going to meet along with any key information or dialogue the company has had with them.

So there you have an introduction to bots covering:  What are Bots? What are Chatbots, Slackbots, Good Looking AI bots?; and Types of Bots.

Reincarnated Loved-Ones Bots 

Microsoft  has applied for a patent on a new bot that effectively reincarnates your loved ones from the data they leave behind – including  voice data, video clips, posts and comments. See Chinese GirlBot With 465m Boyfriends  which has a section about reincarnated bots.  Part 2 explores artificially intelligent marketing bot; How do you create smart AI driven bots? The key to successful bots; taking humans out of the loop? See the more detailed How to build your own bot .

Meanwhile, please let me know if you see any useful bots. Please do post a comment.

If you liked this you might also enjoy some of my other posts:

Chinese GirlBot With 465m Boyfriends 

SOSTAC® Plan for developing your own ChatBot

Artificial Influencers Use My Magic Marketing Formula (IRD) 

Artificial Influencers – Meet Shudu & Miquela

Here Come The Clever Bots – bursting with artificial intelligence? 

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.

Sources:

Bachman, R. (2016) The limits of A.I. and chatbots: How not to fail like Microsoft VB Live, 22 June

Campbell, R. (2016) Introducing DisOrDatBot , Readme.mic, 18 April

Cerny, B (2016) Why chatbots can’t do much more than order you an Uber…yet 22 June, venture Beat

Gartner Predicts (2011), Customer 360 Summit, Los Angeles, March 30 – April 1

McKitterick, W (2016) Messaging apps are now bigger than social networks, Business Insider,15 June

Meeker, M. (2016) 2016 Internet Trends Report, KPCB, 1 June

Rogers, S (2016) Shopify acquires Kit, the artificially intelligent marketing bot, Venture Beat 13 April

Simmonds, R et al (2016) How will bots make money? Here are 7 business models, Venture Beat, 9 June

Smith, PR & Chaffey, D. (2005) Emarketing Excellence, 2^nd ed. Butterworth Heinnemann (bot wars)

Smith, PR (2021) SOSTAC® Guide To Your Perfect Digital Marketing Plan 2021 ed., www.PRSmith.org/books

Suvorov, I (2016) Shopping in messengers, Chatbots Magazine, May.

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