The True Single Customer View

Customer insight has always been central to effective brand positioning and pivotal to any sales and marketing strategy. 

Customers no longer want to be bombarded with irrelevant information.  

With all the pieces of information that brands are supposed to possess at every touchpoint that customers interact with, they should be able to personalize experiences at least.  

Some of the largest brands in the world still deploy old profiling and recommendation models. I call it "fitting the bucket" aspect. Just because a group of users followed a particular pattern in purchases, they got shoved into a bucket. This bucket list of customers all receives the same recommendations, time after time.

It's like drinking from a firehose instead of a filtered pipe.   

The demand for brands to tailor their sales and marketing campaigns in a more personalized way has spurred the need for an in-depth analysis of the customer data. Data that goes beyond the necessary demographic information, but instead developing consumer and customer profiles based on their interests, behaviors, attitudes, and values, applied to things.  

Access to this information has eliminated the need for guesswork and paved the way for more creativity in their data-driven decision-making.

Here we introduce you to the age of the machines, the age of Artificial Intelligence, and Intelligent User Profiling.  

This is what today's consumers look like: 

• 50% of online adults are now blocking ads on their devices. This amount is almost double that reported in 2015.  
• 46% of customers purchase more when personalized across all channels.
• Many brands report an average of 19% uplift in sales that personalize web experiences for their customers.  
• According to Accenture, 44% of consumers are more likely to be repeat customers if a brand provides targeted personalized offers.  
• 40% of customers are more likely to purchase something more expensive than initially planned because of a personalized experience.  
• The list goes on and on.

When embarking on this journey to profiling and recommending nirvana, you want to take the first step, i.e., set the correct baselines for profiling your customers. 

The more data you can stitch together, the more powerful your models will be.  

As an e-business, you will have data from operations, customer services, sales, marketing, finance, and third-party sources; you want to organize and stitch everything. 

Some of the toolsets and external data sets you would also want to use are:  

• Natural Language Processing 
• Visual Recognition Engine
• Weather
• Location Data
• Financial History
• In addition to many others

Start with a single layer of data from a single source and then work your way up the ladder. Think out of the box and find innovative ways in which you could interpret the data you have.  

Several factors contribute to how human beings do things. How we decide to buy products, or go somewhere, or eat something. These factors can be codified into an engine to build a powerful profiling engine that empowers your business to create unique psychographic profiles of each customer. After all, we are all unique individual beings who dislike being stereotyped. Therefore, while building your profiling engine, ensure you do not create "bucket profiles," which will only aid in infuriating your customer.  

Let's talk specifics now.  

Let's say you were a digital bank; you would, at the very least, have the following information on the user: 

• Location Information (from their residential address, workplace address, location information retrieved from their mobile app, location information retrieved from the locations where they have purchased items)
• Weather Patterns (you would be able to pull in weather feeds for the places previously visited)
• Financial Information (the amount contained in their bank account, their spending patterns, the amount of spend, frequency of spend, and many other aspects)

Based on this information alone, you could build a profile that tells you a lot about Sarah Stevens (fictional character).

Here you will find a regular banking app, providing Sarah the basic kind of information that you would normally find in a "modern" banking app.

When Sarah visits a food place, her actions are shared with the bank.

The bank collects all information and once this information is stitched together from multiple divisions you are able to create a profile.

Imagine if your banking system had a dashboard where you could view each individual user's interest in a great amount of detail.

Once you have a profile you could then automate recommendations specifically to her. This would be the perfect storm scenario. The single customer view!

As for Sarah, she would receive personalized recommendations that she would be happy to engage with, as she no longer gets treated like everyone else. She is now special!

&How Intelligence is a specialized consulting house that provides a strategic advisory role to our clients and the operational experience and knowledge required from ideation to implementation.

We help empower corporations to be the next market disruptor by understanding their data, enabling them to change the future.

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