How to Overcome a Lack of Suitable Data

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By: Andrew Long, Product Leader

As consumer brands realize the growing importance of personalization in driving business growth and building customer loyalty, many have awakened to the need for a comprehensive customer data foundation to power their personalization efforts. But two common reactions are “How do I build a solid customer data foundation when we haven’t been collecting customer  data consistently, if at all?” and “With the impending demise of the 3rd party cookie, we have even less customer signals to act on.” Reasonable questions. The good news is, you have more data than you think you do, and there is a lot you can do to create more complete customer profiles with what you already have, all while being compliant with privacy laws.

The data is there, it’s just hard to get to and translate.

Customers provide you with information about themselves whenever they interact with your brand, but there are three common challenges to deal with:

First, the information provided is sparse or inaccurate. Customers transact with your business and they forget to present their loyalty card, have multiple loyalty cards, or simply pay with their credit card without providing additional information about themselves. So, how do you relate these sparse transactional data points to individual customers?

Second, the Information provided is trapped in different data silos. Different customer touchpoints are fronted by different IT systems and are also typically provided by different vendors. When customers interact with a brand at its physical locations, website, mobile app, customer care channels, etc., each system captures and stores data separately. These different technologies all have different customer data models and have no common keys that connect the disparate data. So, how do you bring all this data together cost-effectively and quickly relate the data to individual customers? 

Thirdly, the information provided is inconsistent across different customer channels. Customers interact across a brand’s channels and often provide inconsistent information. Whether they make a mistake with the data entry, their lives change (e.g. getting married, relocating, etc.), or they want to use different contact information for the different channels they interact in — all these behaviors make it challenging to create an accurate customer profile. So, how do you make sense of this inconsistent information?

The answer to all three questions lies in using a first-party customer data identity resolution solution that is able to cost-effectively bring together all the disparate sources of customer data and leave no stone unturned in extracting the available signals, no matter how sparse they may be, from ALL the data, and then intelligently resolving customer identities within that data.

Apply a surgical use of third-party data enrichment.

Once you have a solid view of the state of your customer identities through a rigorous first-party data identity resolution process, then it makes sense to surgically leverage third-party data enrichment where you need it most. To save on cost, and maximize your ROI, you only send the customer records that need to be enriched with additional PII (and other data) to your third-party data provider, rather than sending all records or batches that include records with sufficient data. Then your third-party partner provides the additional data to help with more customer identification or to create richer customer profiles.

"Data collection is not just about collecting customer identification data, but it is also about collecting behavioral data as customers interact with your brand."

Don’t make data collection an afterthought.

Oftentimes, when brands create new digital and physical experiences, collecting data from the customer is an afterthought in the design of those experiences. Data collection should be part of the experience design. The customer should feel like they have received value from the experience so that they want to provide their information for future engagement. 

Data collection also needs to be balanced with the experience and performance requirements of the channel. For example, you are not going to make a customer fill out a lengthy form when they are standing at your cash registers checking out. Doing that would slow down the check-out process and degrade the overall experience for the customer. You need to prioritize which data to collect that is most crucial to your customer identification efforts. You might prioritize first name, last name and email as that combination is often a strong identifying marker for an individual. And if you have to prioritize even further, just getting their email is probably your best bet. It is not only a strong identity marker but also ties the offline and online universes together. Having a customer’s email also allows you to engage with them and progressively ask them for additional information over time, building upon the initial data capture. 

Data collection is not just about collecting customer identification data, but it is also about collecting behavioral data as customers interact with your brand. It’s a commitment to build in data collection mechanisms into the experiences your brand provides to the customer, and to believe it is what will drive continuous improvement of the customer experience and business growth. Amazon is so successful, in part, because they have made understanding their customers (and their behaviors) a foundational step in their internal processes. That wealth of data is what informs improvements to their customer experiences, new products, and new services to offer their customers. 

You don’t have to wait to do this for new experiences and new customer touchpoints — you should look at some of your current busiest interaction channels and figure out whether you can insert light data collection steps in the experience or process that you have today. Remember you don’t have to interrogate the customer, you just have to prioritize the most important data and ask them for that.

Don’t wait for the passing of the third-party cookie.

The death of the third-party cookie is coming soon and its impact to the digital media ecosystem should not be taken lightly. The ability to target audiences and measure the performance of paid digital media will be dramatically affected when the third-party cookie goes away. In recent conversations with some leading consumer brands, I learned that many of them are taking a proactive approach in building out their first-party customer data. Additionally, they are creating internal identity graphs so they have a good view of their customers and how best to reach them. They are building out these identity graphs by getting the most out of the customer data they currently have, and then leveraging third-party data sets on an as-needed basis. With the passing of the third-party cookie, the open question on everyone’s mind is, “What will come in its place that will be privacy compliant and still offer the benefits of targeting and measurement?” The jury is still out. But one thing is certain: building your internal identity graph is a good insurance policy. 

Regardless of what the new digital media ecosystem might be, you will still need rich and accessible customer profiles in order to segment and target your customers. Then, to onboard these targets or to create look-alike audiences in this new digital media ecosystem, you will need to match your first-party customer data into this new ecosystem. Accurate and comprehensive PII data is still going to be key to maximize match rates into the new ecosystem. And if you need to complement your targeting and reach with second party relationships, good PII data is still the critical link to facilitate matching between your and your partner’s customer data.

A final thought to consider.

If there’s one thing I want you to take away from this, it’s that the best time to build out your customer data foundation is right now. Don’t wait until you are too far behind your peers. You have more data than you think you do, and you will be amazed at the data that you find, and the insights you can glean from it.

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Illustration by Nicole Fleming. Artwork generated with the HTML Spirograph by Abel Vincze 2016

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About the Author

Andrew Long

Andrew has 15 years of software product management, digital marketing, and analytics experience with companies experiencing either high-growth or undergoing significant digital & process transformation. Companies range from Amperity, Amazon, Best Buy, Expedia, and Oracle to Atom Tickets and rover.com.

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