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There have been numerous studies that show that AI contrary to conventional wisdom does not in fact reduce employment, rather it creates jobs. Here are my own views and experience of how AI creates work.<\/p>\n
When people think about implementing AI to decision what offer or promotion to present to a customer (in any channel), this simultaneously starts the conversation about what offers they have. In many cases non-retailers will say that they don\u2019t need AI, because they don\u2019t have enough offers or things to say to customers. Conventional decisioning methods like next best offer models or business rules can do the job. On one hand this makes perfect sense, a limited amount of offers, the increase in level of accuracy provided by AI probably doesn\u2019t add much value. The problem is this argument kinda misses the point.<\/p>\n
If you take an insurance company for example, they would reasonably argue that they don\u2019t have many things to sell to a customer; a different insurance policy, an upgrade or some additional benefits. This can be managed by a simple rule or model that says if the customer doesn\u2019t have it, offer it, which might come down to 10 different offers in total.This is what I call the Least Worst Offer (LWO). Even though we go to the trouble of building a model or rules, we approach the problem from the brand\u2019s perspective not the customer\u2019s perspective. It\u2019s not the best offer we can make a customer, it\u2019s the least worst of all of the things we could say.<\/p>\n
The concept of LWO is an important one, because many organisations fool themselves into thinking they are being customer-centric and granted they are better than asking everyone \u201cWould you like fries with that?\u201d. But is it really as good as it gets?<\/p>\n
This is where AI meets job creation in marketing. It starts with the idea that there are 10 different offers or interactions an insurance company can have with a customer. But let me ask you this, if a brand has 5 products, with 10 features each, 3 different pricing plans and 1,000,000 customers, how can they only have 10 different offers? Is it possible to distill that level of diversity and complexity into 10 offers?<\/p>\n
Of course it\u2019s not. In the past we have been working with many constraints, which forced us to limit the number of customer offers, not least of which has been our ability to create and manage a larger range of offers. Then what does AI really do? AI releases resources from the operations of offer management, so that they can be redeployed into creating offers and messages that are more likely to resonate with your customers.<\/p>\n
We, at Digital Alchemy, have created a framework to help you with this. This framework develops interactions aimed at motivating customers based on easy-to-understand psychological techniques, in total there are more than 65 techniques in the framework. Here is an example of how it works.<\/p>\n
Imagine you have a retention offer for a home loan\u2026<\/p>\n
A standard retention offer for a home loan might look something like this –<\/p>\n
\u201cYour home loan is due for renewal soon, renew now for a 0.5% discount on the rate.\u201d<\/p>\n
However, when using our framework, here are some additional propositions based on a handful in the overall framework;<\/p>\n