Predicting how customers might interact with your brand – whether that is making a repeat purchase, reacting to a discount, or defecting to a competitor – helps marketers to tailor their communications with their audience to increase revenue.
For e-commerce marketers, ‘propensity to buy’ models enable an understanding of how likely a person is to purchase from your company. If you are able to ascertain the likelihood of a person purchasing from you before you deliver the communications, then you are empowered to interact (or not interact) with that person in a very personalised way.
Powered by Artificial Intelligence that can make sense of huge data sets, propensity to buy models can personalise the customer experience of your brand – offering the right product to the right person at the right time. In order to do this, these models require three processes to make its decisions:
- Data collection
As with much of digital marketing, a propensity to buy model requires you to bring in a lot of data from the online world: web analytics, advertising campaigns, your CRM, call centers, offline sales, and so on. Here, it is best to include in-depth data on the value of customers – purchase values, frequency of purchases, margin and profitability and predicted lifetime value.
Once you have the right data in place, you need to define the metrics you want to improve so the algorithm understands its objective. You can work towards metrics through the sales funnel, such as lifetime value, or propensity to buy.
Using AI, you can now create an in-depth view of your customers – understanding who is high value or not, who might become a loyal customer and who might defect.
Once the model has been built, you can apply it to a range of marketing activities. You can feed it into your advertising platforms and score users in real-time to upweight or downweight bids based on expected profitability. You can adapt your creative messaging or personalise your landing page based on previous purchases, web behaviours or if they require a discount.
You can also connect with the call-center presenting different phone numbers or even presenting a phone number only to certain customers based on the profiling. Furthermore, you can connect to your CRM system, so the call center prioritizes what order to call on a real-time basis.
We help our clients understand their customers’ propensity to buy with our Gauss Smart Advertising solution. We have seen solid upticks in advertising and sales performance as costs decrease and conversion rates increase.