When Coca-Cola set out to up its data management game and learn more about its customers, the company looked to “cut through the digital noise and clutter” to see people as individuals.
One strategy was paramount: Bring digital analytics in-house to ensure cross-channel integration and insight — a foundation for improving the customer experience.
The soft drink giant shared its story about cutting the cord on traditional vendor-based analytics at an industry event in New York City hosted by my company, which was later detailed in an article in AdExchanger. More broadly, however, Coke’s decision drew attention to an industrywide question facing CMOs and their teams at many brands.
Web analytics solutions had their origins in the 1990s as tools used to measure page views and clicks. Today, they’ve become powerful ways to collect and analyze web data.
But with the proliferation of digital channels and mobile devices, these solutions now stand as just one more data silo requiring integration before brands can get a complete picture of consumers. Many digital marketers today find that their current web analytics solution is just another data source to download daily into an enterprise data store to run through another set of third-party tools for reporting and visualization.
Is it time to re-engineer digital analytics?
Hence the question: Is it time to re-engineer digital analytics and bring this capability in-house to uplevel data strategy?
Industry analysts at Gartner would seem to agree this is a trend in the making. Gartner expects up to 75 percent of enterprises to take a new “build” approach by 2020 in which they say “no” to out-of-the-box vendor applications, opting instead to build more customized solutions.
The potential for replacing a vendor-based web analytics solution with an in-house implementation delivering higher-value uses of data looks tantalizing to many enterprise brands. These are organizations in which digital marketing teams are seeking to use data for more sophisticated analytical insight.
First and foremost, the decision to go in-house with web analytics must be made for the right strategic reasons.
The soft drink company, for example, wanted to better understand individual customer preferences based on a rich collection of first-party data from its highly successful rewards program representing 24 million US households, as well as other sources of data and insight. Data integration was one key factor driving the company’s decision.
Companies considering bringing web analytics in-house need to ask themselves four questions before moving forward. The answers will reveal how important or disruptive switching solutions might be.
1. How healthy is your current web analytics implementation? Is your current deployment properly instrumented and widely adopted? Can you derive meaningful insights across multiple channels?
2. Are you ready to stand up for your own in-house solution? There are multiple steps in this end-to-end delivery, and it’s no small undertaking.
Your enterprise needs a data strategy that is committed to building out these core competencies within your organization around the people, process and tools needed to be successful.
3. Do you understand the full payoff? Your organization needs to understand and appreciate the full potential and long-term upside from the transition to an in-house solution.
The value extracted from data should not be limited to simply replacing your existing web analytics capabilities, but rather you need to achieve broader application of data to drive higher value capabilities
4. Do you understand the trade-offs? Implementations can be complex and time-consuming. You are not going to replicate all the features and capabilities of your current vendor overnight, and you shouldn’t expect to anytime soon.
What’s important is to be clear on the trade-offs between initially losing some features but gaining others of high value to the organization.
Marketers have been concerned for some time about their web analytics solutions as they’ve seen costs rise and ROI, along with utilization, decline. But the desire to reduce costs is not a good enough reason on its own for cutting the cord on a vendor-based web analytics solution.
That decision needs to make strategic sense — and the outcome should deliver improved value in how you use data across the martech stack to engage the omni-channel customer.
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