Customer Data Enhancement & Integration

It's not just WHAT DATA you are collecting, but also how you enhance, transform and integrate it that allows personalization and contextualization that works

PLAN is a four-letter word. It is, for sure. So is FAIL. And what happens with most retailers when they start is they run with their hair on fire trying to capture customers, order inventory, release payments, and not spit nails when a customer says something is navy, not blue.

When it comes to your data, it is the platform of customization, personalization, and contextualization, so if you do not plan for it, it has a higher chance of failing you. And in a crowded retail space, not being able to stand out because “you get” your customers is a recipe for failure.

Collecting data, structuring data, and enhancing and transforming data can take time, and time is a premium for all retailers. Here’s an example;

A customer comes to your website and places an order and the order is converted and fulfilled. The order is placed on 2025-01-18 T01:18:05Z. It’s just a date and time stamp, right?

Wrong.

When you look at the customer 2025-01-18 T01:18:05Z is their first purchase - it’s now labeled their first purchase date that starts the lifetime value clock

2025-01-18 T01:18:05Z - means the offset from UTC zero so this helps you determine the timezone where the order was placed

2025-01-18 T01:18:05Z. T01:18:05 means someone is shopping at night at 1 AM in the morning. A piece of information that can help with fraud detection or understanding a buying pattern of a specific customer.

It’s not just a date when you transform and find the meaning of the date-time stamp to your customer and your business.

There are a few things to think about when you are Enhancing and Integrating customer data and they are broken down into these components.

Data Conditioning

A general rule of thumb is don’t change your source data. Data storage is so cheap, make a copy to fit formats you want or other use cases. But maintain the data element as received at the time of development so your source is always as clean as it can be.

If you store data from Google Forms, or Klayvio Forms or other lead forms, those can go into a spreadsheet, a small database with the provides or sync over to a database you own and manage. The source should be identified during the capture process, as well as the form value, the form inputs, the timestamps, etc. There is A LOT of data in something as simple as a form. Capturing it is a key to personalization and contextualization as to why a customer is engaging with you. As a seller of merchandise, the more you can customize customer experiences, the better the likelihood of conversion and even return buying from companies that “get me”

Data Infrastructure

Your data infrastructure as a young brand is often your shopping cart, email marketing platform, QuickBooks, and ad platform or two. Maintaining the infrastructure is not really top of mind as you build to reach an ideal customer profile and achieve some level of scale and retention.

Don’t think of your infrastructure AFTER you buy it, think of it BEFORE you buy it. Where is data going to reside for us to use it? How are we going to use it? What data will help us sell more and to the right customers to profit more? If you are asking these questions AFTER you choose a platform, you might lose some of the opportunities to collect and store data that could help you along the way.

Online databases are freakishly inexpensive. Tools like Paragon, FiveTran, Integrate io, and others can help you map your data from your cart and POS to a database. Tools like Gemini can help you “write code” to query your data and read the infrastructure you have built. Simple questions like “Can you select the customers who have shopped with us over the last 12 months, aggregate their sales to one record per customer, then sort them in descending order, decile them and apply KEY Meausre to the results?” And that will be it. When you train an ai Bot to help you mine through your data, you can get the insights you need with simple questions rather than having to code. All of that is part of your Data Infrastructure and warehouse tools you can put together for less than $1000 a year that will deliver 100x that in performance.

Data Linkages

Invariable, as your business grows, the more tools you have, the more difficult it becomes to link data back to customers. This becomes increasingly difficult if you do not have your own universal customer id that you can build in a database. One data column that identifies your consumer orders, visits, sessions, service inquiries, items purchased, history, payments used, ads clicked, emails opened and clicked, items configured, etc. Being able to link your data as you go is a key to not having to spend volumes of time and money down the road to sew it back together.

Internal Enhancement

Just as I was illustrating with the data time stamp, how you enhance your data is not how you change the initial data element, but how you describe and leverage that data element to deliver additional value. First purchase date, last purchase date, aggregated 12 months spent, a quintile or decile score on a customer record, a marker for excessive returns, an overall discount rate, and discount dollars consumed. Aggregates and labels help you enhance a simple piece of data into information you can use to make better decisions on offer orchestration, campaign executions, customization, personalization, and contextualization. How you enhance your data goes back to your plan of how you want to manage customer relationships.

Internal data is that these customers bought some things from you. Internal enhancement is categorizing their spend. External enhancement is mapping them to see that they all bought similar categories next to each other. Saturate the zipcode with Outdoor Grills and Kitchens..

External Enhancement

In marketing circles, there is so much noise around external enhancements. And for good reason, a lot of the data is wrong. But external enhancements can also include third-party operational data that can help you improve your data consumption and formatting. Other external enhancements might be demographic enhancements, geographic enhancements, etc. Consider this, If you have lat lon appended to a customer address, you know where they live on a map. How cool. When you plot them you can see, hey, some of these customers are clustered together and their orders are clustered together. Hmmm.. maybe neighbors are talking about your brand. Data analytics can help you find that. External Enhancements can tell you the average home value in that ZIP code is $850,000 and now you know you have found affluent high-value customers with discretionary income.

Embrace Contextualization with First-Party Data

There is a proliferation of retail brands. Cutting through the noise, resonating with customers, resonating with neighbors having summer BQ cook-offs, and understanding their why they buy as much as what they buy is going to enable you to stand out. Don’t be afraid to use multi-step forms. CRO’s are going to tell you they break. And they just might. But you are after QUALITY buyers, not cursory ones. And those who take the time to engage want to work with you. That’s a level of intent to buy you cannot get from third-party enhancements. You get it directly from the buyer. And it’s 100% a better way to sell.

It’s 2025 - spend some time putting your data architecture in place. Revisit how and what data you collect. Revisit top-tier customers from 2024 and find out their why along with their what. Customers will engage with you if there is something in it for them. So build collections and products around them using their own words on WHY they buy what they did.