8 Steps to Build a Customer Intelligence-Based Data Plan
*This article was originally published on Adweek.com on May 21, 2018.
It’s impossible to open any industry trade publication these days and not see a headline about data. It’s the new oil. It’s the source of all competitive advantage. It’s under fire with GDPR. It’s private, public, shared, opted-in and opted-out.
But data is not just a commodity. It’s our modern-day DNA. It helps us understand people. To know them and serve them. Data helps brands get closer to their customers and prospects, what marketing has always been about, whether it’s at the corner store or online.
Brands that have reframed their purpose around creating meaningful and transparent customer relationships are the ones that are set up to succeed. Not because they have more data, but because they have more intelligence.
The key to rewiring your business around people begins strategically: How can you build a more direct relationship with your customers? What do you have of value to offer them? How can you use data to enable that value and is it worth the value exchange required? How does this advance your customer relationships and how can you now serve them with greater care, personalization and distinction?
This people strategy requires knowing customers for their fully connected experiences — not just online or offline — by resolving everything you know about them to a single identity. People don’t make a distinction between their digital and physical lives, so neither should you. If they want to buy online, great. If they want to buy in-store, great. If they want to browse online and buy in-store, a smart retailer should be able to marry those two experiences to make them easy and frictionless.
Once your strategy is in place, follow this eight-step, customer intelligence-based data plan to help your brand recognize, serve and delight customers:
1. Ensure that any data collected is aligned with stakeholder needs
What business problems are you trying to solve? Who are the key stakeholders using the data and how does that data need to be collected, cleaned, corroborated and connected?
2. Set up a governance plan
Privacy by design should be at the core of any data-enablement strategy, with good responsible governance as a foundation. Bring your IT, legal, and privacy teams together to create sustainable policies around data collection, processing, and management. And never collect data for the sake of having it for future use – if you don’t have a plan and policies set up in advance of any data capture, go back to step one.
3. Vet, cleanse, and format your data
Since your goal is to get a good connected view of your customer, you’ll want to establish that your data is correct, clean, and formatted so that it can be matched with other attributes and signals. You need to recognize the sources of inaccuracy in your own data — consumers mistyping information, purchased data that’s been poorly vetted, or simply the impact of time as consumers move and change email addresses or phone numbers — and work with a partner to identity and resolve these issues.
4. Resolve to a single identity
This is the hard part. To resolve multiple fractional profiles to a single identity, you need a partner with a robust identity graph — one that provides a single unified 360-degree view online and offline, across channels and devices, that is accurate, persistent over time, and works as a durable match key underlying all use cases you are looking to employ. This identity then maps to everything from upstream customer intelligence and segmentation through onboarding and activation through all of your measurement efforts, then feeds it back again to make your activities smarter, more effective, and more efficient. An end-to-end system of identity is the key to successful data enablement.
5. Turn data into intelligence
You may have zettabytes of data, but if it doesn’t help your company better understand and serve your customer, it doesn’t matter. Analyze your data for new insights. Visualize data sets to make these insights spark to life. Partner with your data science team to map your customer data against exogenous factors to find hidden drivers for your brand.
6. Act against that intelligence
Once you’ve established a relationship with your customers, reward them for their generosity. They’ve shared something of value with you, it’s your job to pay them back. If they let you recognize them, serve them. Provide them more meaningful interactions. Engage them in their preferred channels. Thank them with special offers or simpler ways to buy. Don’t just expect customers to be loyal — be a loyal-to-your-customers brand.
7. Stay up-to-date
Your customers change all the time. Make sure you maintain an accurate, up-to-date identity, taking into account changes in address, emails, devices, name or age. An always-on identity management plan captures and resolves changes to customer identity as they happen.
8. Finally, optimize and repeat
Brands must continually improve customer experience or risk imminent disruption. As your brand evolves, so must your relationship and data strategy. It should be a continuous feedback loop. Never stop improving your programs based your one-to-one relationship with your customers.
Today we are able to take arm’s length, once-opaque, relationships with customers and make them direct and transparent. We are able to understand our customers and prospects more deeply, so that we can serve them better. And we are able to measure what worked and didn’t, so we can continuously improve. Data is full of potential for marketers who use it to smooth frictions, and create more meaningful, valuable customer experiences. Marketers who succeed recognize that data is only good as the people it helps them to serve.