You don’t know your customer anymore

Traditional algorithms cannot help in predicting purchase behaviors today because they are based on historical data. Behavior change brought about by Covid19 invalidates much of this data.

How can brands effectively reach customers today and personalize engagement across channels? Reflecting on this challenge, my thought went to ActionIQ – intelligence hub that enables the delivery of personalized experiences at scale. Tasso Argyros, its co-founder and CEO, thinks differently and thinks ahead. Here the highlights of our conversation last week.

FD: In a recent article* Mark Payne, co-founder and president of Fahrenheit 212, urged businesses to take all the insights you’ve gleaned from years of mining the gray matter, hopes, needs and behavior of your customers, shove them in a proverbial file, and start over. What do you think about it?

TA: I think it’s a great point. Think about AI today: it’s data science algorithms. Algorithms need to be trained on historical data. What’s happening is that all the historical data reflects behaviors that are no longer there. Hence, all the algorithms based on that historical data are useless right now. It is scary but that?s the reality. The beauty of a customer data platform (CDP) is that the data and the models live in the same place, therefore the models can be retrained with data from the previous month or even week, in a very agile way. If your customer behavior changes, you can press a button and we re-train your models. If you don’t trust the models, you can look into what’s informing them and draw your own conclusions. The sooner people accept the fact that all the models they have deployed are useless, the better it is, because they need to get going, shift their focus from the models to the new data and use a more agile platform to action it.

FD: Tasso, can you clarify what customer data platform are and why there is so much interest around them today?

TA: A CDP covers the last mile: it makes the customer data that is inside a company visible and accessible for marketing, sales and customer servicing purposes. Leveraging this data to improve customer experience is a massive challenge. The growth of the costs of customer acquisition and the shift towards increasing customer lifetime value have made CDPs very hot.

FD: Absolutely, building customer relationships is paramount and crisis add a sense of urgency. How does ActionIQ stand out, what makes you different from other providers out there?

TA: A lot of companies claim to be CDPs because they leverage some customer data, but they are more ecommerce specific companies or point solutions like web and email personalization platforms. Their main limitation is that they take data from just one channel to personalize only that channel. The difference with ActionIQ is that we take data from everywhere, any system and source a company may have, online and offline, and we can then push data into web solutions of any kind, but also email, direct mail or even analytics systems to enable further analysis. We are the only company that can pull data out of data lakes in the order of terabytes. It is a very complex task that requires a product that can scale and that understands how the data is structured. We are totally channel and function agonistic and believe that this is important because to provide a truly better experience you have to be wherever the customer is and take into account all of their past interactions with you.

FD: And the platform learns from activations and campaigns, correct? Can you tell me more about AIq Artificial Intelligence and your vision for it?

TA: AI is a big part of our platform; it is essential to enable personalized experiences. For us personalization means taking into consideration the individual journey and intent of every customer. Think about Amazon, that uses a traditional algorithm for recommendations: people who bought this product also bought these other ones. The personalization happens at product level, which means that you and I can have a very different purchase intent, very different journeys and destinations linked to this purchase, but we both get exactly the same product suggestions. What we offer with ActionIQ is the ability to understand the full picture and predict where each individual customer wants to go next in their journey. This allows diversification of suggestions/communications/activations.

FD: How can you claim that Action IQ is the fastest path from customer data to personalized experience at scale? It is quite a bold and enticing statement.

TA: What takes time and constitutes the biggest risk when you are deploying a solution is data not being in the right format. We remove that risk as we can process data in any format. We work in a very agile way and can deliver results very fast, 6-8 weeks. We have the best time to value in the market. As a response to Covid19, we have developed a plan that can be executed even faster.

FD: That’s fantastic. What is the effort required, company side?

TA: It’s actually not significant. We have shaped a team of experts both on the use case, marketing side and on the data science side. We run a value optimization workshop for prospect customers, free of charge. We help them identify their primary goal, e.g.: improving retention, moving more people from physical to digital channels, trying to sell the same number of products but with better margin. Then we look at the channels that can help them get there and focus on the required data, wherever it may be. Having clarified goal, channels and data, we develop a plan that can be executed in 4 to 6 weeks.

FD: How can your platform take into account external data, like macro-economic or environmental data?

TA: AI cannot replace the marketer. There is always business context that is not reflected in the data. The future of business is in the interaction between humans and AI. What we have developed, to facilitate this interaction, is what I call a white box model, in contrast with the traditional black box model algorithms. Black box refers to the fact that they can predict what your customers want to buy next, but there’s no visibility into how the algorithm is making that prediction. The engineers who built the algorithms are the only ones that can influence them. Transparency + flexible user interface are the principles on which we have built our AI, a white box model. With ActionIQ a businessperson can understand why an algorithm is driving certain conclusions, what data and patterns inform it. They are also able to influence the algorithm with business context e.g. bad weather coming, inventory shortage.

This was originally published on Linkedin. Read full article here.

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