Increasingly, companies have turned to customer data platforms (CDPs) to help them run more relevant marketing campaigns using the large volume of customer data at their fingertips. Join this VB Live event to hear how one company harnesses customer data to run complex marketing campaigns that increase sales and loyalty.
The proliferation of martech tools has been a great boon for marketers — until the sheer number of them considered “essential” for staying competitive started to pile up and overflow. SendGrid for email, Facebook ads for online advertising, analytics from three other tools. The result: separate customer data silos, because of course most of these companies don’t particularly have a vested interest in integrating with competitors’ tools.
Customer data platforms emerged as a way to create a neutral hub between all of your martech tools, giving you a single, unified customer view and enabling incredibly sophisticated targeting that wasn’t possible before.
Companies like Heineken, The Economist, Atlassian, General Mills, have all been early adopters of customer data platforms, such as Lytics, enabling them to ramp up their marketing power, says Jeff Hardison, VP of marketing at Lytics.
For instance, you can create a segment of people as specific as those who have unsubscribed from your email newsletter but still interact and engage on social platforms, in order to retarget them with advertising. And that’s just the start — you can also personalize your actual Saas products, Hardison adds, like in-app messaging platforms.
“Maybe you’re the champion that brought on JIRA software into your organization or HipChat — and maybe I was the laggard who’s never logged in,” Hardison says. “Atlassian can use a customer data platform to personalize interactions with me, maybe to nudge me along to use the software, or maybe to check in with you to make sure that you’re happy as the champion of the software.”
The machine learning that customer data platforms are built on allow you to score all of your users based on their ever-changing affinity for a brand over time, too — far beyond what an email marketing automation tool can handle.
“I could say, ‘If the person has visited the website in the last 30 days and if they’ve clicked on an email in the last week, I’m going to call these people highly engaged,’ but we believe that that’s too simplistic,” Hardison says. “You can use machine learning to look at more than 200 factors about someone’s behavior to see if they’re highly engaged across marketing channels. And only machine learning can do that, not humans and their gut instincts about what is highly engaged.”
CDPs can also add content to the predictive marketing mix, uncovering what kind of content is driving user interest and prompting their journey across your site. Today, humans do a lot of that tagging manually on websites, but it’s a time-intensive gig. Machine learning allows you to match which individual subscribers like which particular articles, and be able to make recommendations to customers based on that.
“For example, General Mills is doing that within their email newsletters,” he explains. “They use Silverpop to send emails and they drop a tag into the Silverpop email template to make recommendations for say, various recipes from their website. You know, if you like this, then this content right here is recommended just for you.”
Building an in-house customer data platform is possible — especially for software companies with talented developers on staff. But off-the-shelf solutions tend to be far more inexpensive, and far more integrated.
An off-the-shelf CDP solution should have already built the identity resolution technology to stitch together your graph database and identity fragments, plus have the machine learning capability in place to score people on whether they’re highly engaged or slipping away, and a content affinity.
“They’re seeing that meta CDPs already have in place a lot of the product features and the stability and the scalability, and so it makes more sense to choose something that’s off the shelf versus building their own,” explains Hardison.
For more on making the decision between home-made and store-bought, the marketing campaign complexity at scale that customer data platforms can deliver and more, don’t miss this VB Live event!
In this VB Live event, you will learn:
- Key considerations when deciding to build versus buy a customer data platform
- How companies are taking advantage of CDPs for more relevant communications
- How data science can improve marketing efficacy
- The trends and market factors driving the need for customer data platforms
- Jeff Sinclair, Product Manager, Engagement Platform, Atlassian
- David Raab, Analyst and Founder at The Customer Data Platform Institute
- Jeff Hardison, VP of Marketing at Lytics
- Stewart Rogers, Director of Marketing Technology, VentureBeat
Sponsored by Lytics