Artificial Intelligence, marketing and being a dummy

When I feel I’m out of my depth, or I stumble across an innovation that I need a quick heads-up on, the “For Dummies” series of books is often my go-to resource. It seems though that, unlike Quantum Physics or Neuroscience, Artificial Intelligence (AI) is not something that can be significantly “dumbed down” enough for a simple marketer like me and that book is still to be written!

But being curious and, as it’s a topic that’s increasingly appearing in marketing newsfeeds, we’ve undertaken some research to come up with our quick reference to AI and seven of the marketing applications and uses that are growing ever more prevalent.

Overview

This Alan Turing definition is a good place to start “Artificial Intelligence (AI) is usually defined as the science of making computers do things that require intelligence when done by humans”. But the Beeb has a neat little video that explains what the devil AI actually is (here) and supports that with a timeline of “15 key moments in the story of artificial intelligence” (here). Useful grounding before diving in to the detail below.

1. Product recommendations

Use Amazon? Of course you do. Then you’ll be familiar with its “predictive analytics” and product recommendations based on your searches and past purchases. It uses a clustering algorithm to make and improve suggestions learning and finessing those the more you visit and act on them.

2. Chatbots and “virtual PAs”

Alexa, Siri, and Google Assistant are probably the best known with even the tech-wary finding uses and benefit from them. Talking or typing to a chatbot delivers a service using a combination of natural language and an understanding of a brand's datasets.

3. Customer Segmentation

Slicing and dicing a data set using demographic profiling to segment it and market to it more effectively is a classic marketing tool. AI takes this to the next level. Using a raft of indicators across first and third-party data it can see patterns and preferences and make predictions, and continually learning from user behaviour, segment data faster and in a smarter more effective way.

4. Search engines

Machine learning was pioneered by the likes of Google to provide search, advertising and YouTube recommendations. It has recently revealed its use of an AI system called RankBrain to interpret a 'very large fraction' of search queries and using context and natural language processing (NLP) improve the results it delivers.

5. Dynamic pricing

Stock levels and supply availability, trends, demand and seasonality could and should impact on the price of goods or a service. Too many factors to correlate manually, AI can be used to optimise the individual prices and economic order quantities of products. So, a slow-moving item coming to the end of its shelf-life might be proffered at a knock-down price for a limited period.

6. Predictive customer service

Understanding how a customer might prefer to interact and their choice of channel helps plan resource and guides them gently along their personal “customer journey”. Take the example of a mobile phone user with a service issue who always opt for online chat to resolve it. Offering that as the primary and personalised option reduces the resolution time and improves customer experience.

7. Ad targeting

Whether you decide to click or not, you’ll recognise that increasingly the ads that are served to you on the websites you visit are a direct result of your browsing history and shopping preferences. AI is in play to maximise the chances of you buying and the advertiser reaping the benefit of his programmatic ad spend. 

These seven are just for starters. Image recognition, translation services, fraud detection – these services and many others are being powered and fueled by AI.

This particular Dummies book is going to be a weighty one by the time it’s published!

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Jon Tolley

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