Marketing analytics: how to overcome the tech bottleneck

Remember the days when marketing was a calm, cool environment where a good set of customer analytics would tide you over for a month’s worth of strategic, data-driven decisions?

Yeah, neither do I.

Today customer behaviors, preferences, and attitudes can change at the speed of light, and marketing teams need to move — and pivot — no less quickly. The good news is, in this era of big data marketing, there’s no shortage of data to inform and guide those day-to-day (or hour-by-hour) decisions. The less-good news is that most marketing teams don’t have dedicated data scientists and data engineers. They must often rely on their overburdened, backlogged colleagues in IT to spin that data into actionable information and deliver it in a usable format … and wait for it.

It’s a conundrum that plagues organizations across industries, and fortunately, there is a solution. When we work with clients to empower their marketing teams with the data tools they need to be more agile, we focus on three facets: improving the data structure, creating a standard reporting system, and building a nimble, scalable framework.

1. Improve the data structure

When we work with clients, we focus on two key deliverables at this juncture:

  • Stage the reporting data: Make sure the data is structured to be used effectively by the analytics reporting system.
  • Ensure accessibility: Integrate the analytics platform to ensure automatic flow of data when and where it’s needed.

2. Create standard reporting

The ideal reporting tool will spin the latest marketing data into action-oriented insights that enable more strategic business decisions. For example, the following dashboard could guide a marketing team’s next steps in optimizing their commercial website for maximum traffic:

3. Build a nimble, scalable framework

• Multivariate testing allows marketers to test the results when certain variables are changed, such as the layout of a landing page.

• Cohort analysis enables the team to track the behaviors of a specific set of users (e.g. long-term customers) over specific periods of time to determine which approaches resonate best with them.

• Funnel analytics gives marketers the opportunity to review and redefine the customer journey — to test hypotheses and see where users actually go for content, and to update their journey flows accordingly.

Personalization lets teams dynamically retarget content and test to see which actions are driving users to the next phase of the customer journey.

When the marketing team is empowered with a self-service analytics framework, they have their own “experiment engine” that lets them evaluate any number of possibilities:

The marketing team is then free to play with different ways of combining and viewing their data and to evaluate the results of experimental initiatives, such as a pilot campaign for a new marketing channel or a new data source. We work with our clients to create a structure for ad-hoc reporting, creating a rhythmic framework for shared learning and experimentation that will continue to serve the team as their environment evolves.

New platforms, new possibilities

To view more images and a real case study from Logic20/20, view the full article here: https://www.logic2020.com/insight/marketing-analytics-overcoming-tech-bottleneck

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