Six marketing data challenges (and how to tackle them)

“This year will be all about AI.”
“And don’t forget podcasts!”
“And blockchain, live video, and social commerce.”

Every marketer has been a part of this meeting of roundtable buzzword BINGO. Everyone around the table suggests investing in a different part of the market’s most buzzworthy tech. All you have to do now is buy all these industry-leading technologies, give them all your “big data,” and you’ll immediately set your brand apart to lock in that sweet raise when the revenue comes rolling in. Easy.

In reality, you leave the meeting with more ideas than executable options, a list of technologies to invest in (which may not fit your marketing budget), and a mild case of “what the heck just happened.” Lucky for you, you’re not alone.

During his session at MarTech West in San Jose, Jason Mestrits, senior manager of data science and analytics at Nordstrom, shed light on the challenges facing marketers looking to follow a data-driven strategy. While tactics like nano-influencers and social commerce sound great to stakeholders (who love buzzwords), it’s important to remember these tactics are nothing but fluff without diagnosing data and creating a methodical data-driven strategy to back them up.

Mestrits outlined a few key steps marketers can move toward to ensure an effective data-driven operation is in place.

Define use-case data strategy and technology that scales

The best data-driven marketers follow a use-case-based strategy that takes data, analytics, insights, integrations, and puts them on top of the corporate policies in-house. This means marketing needs to ensure platforms/partners they are investing in are ready to scale. It’s tempting to select the least expensive platform or one that supports only the current need, but considering the resources required to implement a platform, it’s often more cost-effective to select a long-term, cross-team solution.

Select the right data resource platforms

Mestrits recommends a customer data platform (CDP) over a data management platform (DMP). While a DMP simply collects, categorizes and segments data for marketers to target customers, CDPs go further by gathering data from across sources to help marketers create customized content.

Segment and target your audiences

Third-party data tends to be easiest to obtain because marketers can simply purchase it. Meanwhile, first-party data holds the most value because it comes directly from the customers themselves. Marketers should overlay both sets, starting with first-party behavioral data, to develop the most effective strategies.

Maintain high-quality data

Data-driven marketing is only as effective as the quality of the data used, underlining the importance of good data hygiene. Quality control measures, such as alerts for outdated lists and ongoing checks for duplicate customers are some easy, proactive steps to ensure good data practices. It’s also important to avoid silos and practice centralized data hygiene across marketing teams to prevent conflicting records.

Track the right metrics

To ensure a data-driven marketing strategy is effective, measure it at multiple levels not just at the channel or product. This is where a cross-team solution can prove its worth, showing that it can meet the specific needs and objectives of multiple departments. Start by deciding what outcomes to measure, and how to drive the measurement conversation throughout the organization. Marketers sometimes feel that they need to track every metric, but it’s better to do so selectively. Focus on KPIs that incentivize target behaviors, engagement, conversion, loyalty or another goal like efficiency.

Long story short, the buzzwords aren’t going away anytime soon so marketers who champion a methodical data-driven marketing strategy will own conversations and limit playing buzzword bingo in their marketing planning sessions.