A shopper visits your showroom, goes to your website and joins your email list. She eventually buys six of your products—some at your store, others at a big-box retailer. She also calls your help desk and downloads your mobile app.
Now for the hard question: Can you look across those interactions, and recognize that each engagement came from the same person?
If your brand is like many others, you might not be able to map out that customer journey. And the reason may stem from a deeper problem: You can't identify the customer.
Solving customer identity issues is key to successfully knowing and responding to customer journey interactions, but before you can fully and accurately know your customers, you need to take a good hard look at two common customer data quality challenges.
Challenge No. 1: Siloed Data
It's likely that your brand records customer engagements differently based on the channel. You might track digital ad engagements via cookies; digital marketing via email; and help-center calls by phone number. To understand a single journey across all those touches, you need to connect these records across the silos—matching the cookies, emails and phone numbers to a persistent customer ID.
Easier said than done.
One problem is organizational. Aligning workers across teams to sync data collection methods, KPIs and systems is time-consuming, challenging and may be perceived as a threat. Between inertia and fear, there's not much incentive for teams to carve out time to sync the data.
There's also the dizzying technical challenge of aligning systems. CRM alignment is a good example. Each silo might have its own CRM system, or multiple ones with different ways of identifying and describing the customer. More systems can mean richer data—but wrangling all that system data into a single view can be a Herculean task.
Add in channels that seem like they should connect but often don't—like online "walled gardens," plus the surprisingly distinct data universes of mobile email and mobile apps—and you begin to see the hard truth: Data silos are a problem that won't easily go away.
Challenge No. 2: Incomplete Data
It's not just that brands struggle to identify customers across silos. They struggle to get accurate customer identity data within silos too.
For starters, even the "best" data may not be accurate forever. Between email-address changes, 30-day cookies and the millions of Americans who change phone numbers, addresses or their names annually, it's no surprise that 60% of customer identity data is outdated within two years.
But while the identifiers rapidly expire, brands rarely keep the data up to date. Instead, customer data often goes into the CRM system just once—when a customer self-identifies at a significant interaction, like a sale—and never gets updated again. If that same customer comes back to make another purchase, but uses a different identifier, he or she is often entered into the system again, but as a completely new record, causing confusion and increasing data management costs.
Plus, a great deal of customer data is inaccurate to begin with. Think about all the times you have provided the wrong email address, phone number or other personal information to a brand when making a purchase. Now extrapolate that across the millions of records housed within your CRM.
Put it all together, and brands may not know much about their customers.
Take Three Steps Forward
Recognizing the problems with your customer data—and the way your company manages it—is crucial to your ability to turn those challenges into an opportunity to do truly customer-centric marketing. But to be able to follow your customers along their journey, and to personalize and enhance marketing efforts accordingly, you must prioritize these three factors:
1. Focus on the customer—not the data.
Don't chase data for data's sake. Develop a data strategy focused on identifying, understanding and creating experiences for the customer—the real individual who has many interactions across many touchpoints and who is constantly changing.
Being customer-first, not data-first, means starting with what you already know about the customer and using that data to fill in that picture. Focusing on quality over quantity will allow you to collect more accurate intelligence from those consumers who actually want to engage with your brand. It will also require evaluating the quality of the data and data management provided by external partners. Understand where it comes from, how often it's updated, and how it is being used to enrich and repair your own records.
As a bonus: By educating yourself on the data practices of your partners, you can better prepare yourself when outside factors like GDPR and other privacy regulations seem to get between you and your customers. The more you know about where your data is going and how it is getting there, the better prepared—and safer—your organization and your customers will be. The potential cost is simply too high, both in terms of GDPR fines and customer loyalty, to risk working with a data partner that does not have a proven privacy-by-design track record.
2. Redefine your organization around customers, not channels.
Rather than gathering identity data piecemeal across silos, work toward a single version of the truth. This means connecting the omnichannel dots across the customer's journey, from offline to online, from acquisition to retention.
Mobilize the C-suite to guide teams beyond their comfort zones, and to commit to the hard work of customer-centric data alignment. And if you're working with a partner to get that omnichannel view, be sure it's a neutral partner—with no vested interest in promoting any one media channel. And make sure they can actually activate that data across channels. An omnichannel view won't help if you aren't set up to use it.
A great example of customer-led omnichannel marketing is the Coca-Cola Freestyle app, which lets consumers custom-design drink mixes, and purchase those mixes at Freestyle-supported locations. It connects customers' drink preferences to a point of sale, and fills in crucial information that a CPG brand like Coke might not otherwise be able to access.
3. Act now before it's too late.
Given the inaccuracies in customer data, it's essential to make sure your data is in good shape. Data proliferation and fragmentation are only going to accelerate.
Assess your existing data, and pinpoint what's wrong and what's missing. Clean, repair and complete your records, and ensure your customer data is constantly refreshed. Enrich your data with additional insights before taking action—like demographics, psychographics and location insights. The more you know about your existing customers, the greater your ability to optimize their experience with your brand along their journey.
Fixing the data you have benefits your entire organization, which most likely depends on this intelligence to operate.
- Consolidate your customer view at the enterprise level.
- Use authoritative linkages to recover the data value lost due to fractional records.
- Dynamically monitor and react to customer-buying signals and changes in their journey.
- Analyze and connect all customer signals as they become available.
Taking the necessary steps now will allow you to future-proof your customer data for the "journey" ahead.