Breathing Life Into Your Cross-Channel Analytics

Five best practices for establishing enterprise-level insight across marketing channels

As the power of information continues to shift away from institutions and toward customers, we need to modify the way we address our prospects and customers to stay competitive. Personalized cross-channel marketing experiences will soon be an expectation from our customers and every day spent ignoring this reality is a day of lost insight into customer preference and, in turn, lost conversions or loyalty.

Those who will win in the next generation of advertising will coordinate timing and messaging of their display, social, email, site, and relationship marketing while also personalizing all of it to the preferences and location in the marketing lifecycle of an individual.

In a recent case study from Adometry, for example, Lenovo doubled down on marketing attribution technology and infrastructure and drove strong insights around how to optimize marketing spend to better reach and engage its audience. A few of the key takeaways included:

“The percentage of revenue resulting from multi-touch conversion paths (75%) as well as the extent to which engagement spanned multiple channels (48%) means consumers are being reached by multiple programs and a variety of channels within Lenovo’s mix.

“When looking at channels by funnel stage (introducers, promoters, and closers), the channels that act as closers offered no surprises. However, Lenovo didn’t realize how much branded display, paid social, paid search, and organic social are responsible for taking prospects to the next step as introducers and promoters in the conversion path. Armed with a new view of performance in these channels, Lenovo will optimize investments and drive greater sales.”

This may sound like a daunting task, particularly when already struggling to do this within a single channel, but marketing technologies continue to progress and perform most of the heavily lifting when built on the right data infrastructure.

Here are some tips to help your organization bite this off into more manageable pieces:

1. Seek clarity on goal alignment
Understand, document, and align your channels on a set of goals that align to your overall business objectives and let this inform your technology and data-onboarding investments.
Between the different options among marketing tools for data import/export/merging, data granularities, data caveats, varying unique user IDs, and more, it’s easy to get hung up on the challenges of tying all marketing channel data sources together. Instead, build a prioritized plan for investment in onboarding the channels where you either A) spend the most money and/or B) require the lowest investment to integrate into a unified data set. This exercise can also be used to uncover data “blind spots” or current reporting/technology gaps.

2. Extend the data olive branch between teams
Don’t get hung up on inefficiencies of organizational structure. Use cross-channel analytics investment to drive cross-channel marketing collaboration.
All too often within large organizations, individual marketing channels are owned by individual marketing teams. This structure tends to proliferate the data and digital experience silo and leads to a sense of “we aren’t organized to act on data like that, so why try?” Instead, adopt a “better together” mentality and leverage cross-channel analysis and insights to drive cross-channel testing hypotheses and, in turn, unified and personalized cross-channel digital experiences.
In addition, don’t rely on representatives from each channel or another centralized analytics team to prioritize time to develop a cross-channel analytics program. Building the program should be the primary focus for a team of FTEs and, ideally, specialized agency/vendor representatives.

3. Quit waiting for someone else to do it
Marketing should drive cross-channel analytics initiatives, including infrastructure. Don’t wait for IT to build the capability. Cross-channel marketing analytics isn’t (and shouldn’t be) a priority for them. With the influx of data and re-platforming of data transformation and storage solutions happening across all industries, IT has their hands full for the foreseeable future. If they won’t be ready to support marketing data integrations in the next three months, don’t wait for this one-solution-fits-all to be completed to start analyzing cross-channel data. Provide your long-term requirements to IT, then leverage any number of automated cross-channel analytics/attribution technologies and vendors to stay competitive and retrofit once the capabilities are available in house.

4. Look for secondary use cases throughout your organization
Cross-channel analytics infrastructure can be extensible for a wide range of marketing analysis activities including customer journey mapping, user segmentation, marketing attribution, predictive modeling, and many more. The initial setup is the hard part and can be the foundation for transforming your marketing organization.
As you begin building your data set across different channel data sources, don’t just explore one avenue of analysis. Even if your cross-channel analytics goal is focused around one output, devote some resources to exploration of other business/marketing questions.

5. Find the early wins in your acquisition funnel
At minimum, prioritize understanding which channels are best at driving activities within different stages of your marketing lifecycle or acquisition funnel.
This doesn’t always require complex attribution algorithms or hefty technology and infrastructure investments, but it does require an understanding of your marketing lifecycle or acquisition funnel and the measureable KPIs that are captured at each stage.

Knowing this alone can drive not only more effective collaboration in campaign and evergreen marketing planning, but can also begin realigning the business to be able to act on and prioritize cross-channel data investments.