Quality customer data is the beating heart of every successful marketing campaign. That information is what allows you to narrow the opening of the funnel enough to make sure your campaign lands in the right hands, to either shift a mindset or cater to a need.
By identifying and marketing to your target audience, you save your potential buyers the headache of bumbling through goods and services that don’t apply to them, looking for what they need. And you don’t waste their time by pestering them with irrelevant ads. Knowing your audience and having the right customer data in place to execute relevant campaigns is the critical step up and away from the “spray-and-pray” marketing approach of the past.
Take personalized content for instance. Personalized content, like emails and offers, increases engagement, leads to more customer loyalty and allows you to build an authentic connection with consumers. This, in turn, leads to higher conversion rates. Personal, individualized ads always perform better than those targeted at a wide audience.
So, how do you get the data necessary to truly know your audience?
Customer data in hand
Let’s start with what you already have. Maybe you have a collection of email addresses and names—you may even have a customer database. This concrete information helps you know who your audience is at a basic level. This can also include personal identifiers like phone numbers, account usernames and even offline data like a physical address.
These identifiers, including account logins and user profiles, make up deterministic matching. However, what deterministic matching lacks in scale (not all websites require a user to login or input an email address), probabilistic matching makes up with its wider scope.
Probabilistic matching, though not 100% accurate like deterministic matching, can identify interactions across multiple devices such as browser activity, IP address, location and purchase history. Perhaps you have most of the deterministic fields complete, but you don’t follow your audience through probabilistic matching. Or maybe you employ a combination of the two but you’re still missing fields for individuals. These specific details—like the car model they own or the TV programs they watch—can truly elevate a campaign.
There’s a lot of data you can mine. And a lot of the time, consumer preferences, email addresses and physical addresses change quickly and unexpectedly. This makes real-time updates as important as how comprehensive your data is.
Address the gaps with identity graphs
Today’s real-time identity graphs can address these gaps. An identity graph uses both deterministic and probabilistic matching (of identifiers and interactions) to match an individual across multiple devices.
A valuable identity graph has everything you could ever want to know about your marketing audiences, but it is important to know where that data is sourced. It could be online data sourced directly from an in-house email service provider (ESP) and demand-side platform (DSP) and then verified by a third-party dataset.
Some data providers will offer to help data strategists conduct an in-depth audit and analysis of existing data assets to discover gaps, missed opportunities and lost revenue. This is critical to building complete views of customers and prospects.
Look for a partner that offers flexibility on how you want to use the data and can deliver complete solutions from visitor identification, audience creation, omnichannel campaign execution and reporting.
Identity-level data is as mission-critical for today’s brand marketers and agencies, as is being able to onboard and execute omnichannel campaigns quickly and easily.
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Ajay Gupta has been CEO of Stirista since founding the data-driven performance marketing company in 2010 and has overseen the company’s rapid year-to-year growth. He has been named a Marketing EDGE Rising Star and was part of the San Antonio Business Journal’s 40 Under 40 list.
