Now that we are aware of what not to do let’s dive deeper and talk about methods to handle these common pitfalls:
1. Take the time to write a short letter
Analysts must distinguish between what is ‘nice to know’ and genuine insights; the latter must apply to business objectives and demand action. We’re analysts, and even we aren’t patient enough to read through long emails or extensive PowerPoints full of data points and graphs. Imagine how your marketing team feels. It’s OK if you don’t have all the answers; providing relevant and meaningful insights will naturally spark a discussion, leading us to tip #2.
2. Facilitate ideation and next steps
It can be challenging to advise marketers without seeming overly directive. Not to mention, there isn’t always a single, straightforward answer. Too often, analysts present findings and expect everyone else to figure out what to do next. You have to work together as a team. Talk about what you found, theorize why it could be like that, brainstorm solutions, put a plan in action, and evaluate the results. That’s how to use marketing analytics properly.
3. Don’t introduce uncertainty
We all know marketing data can be incomplete and slightly inaccurate. Still, it is rarely so unclean that marketers cannot derive valuable insights from it to guide decisions. As an analyst, you may be aware of the difficulties in the data and want to add warnings about not interpreting the insights as absolute truths. Unfortunately, this can lead to skepticism from people who don’t understand the nuances. If you believe your insights are dependable, ensure your work communicates that. Don’t undermine your findings with language that deters people from considering what you have found.
4. Tailor your output to your audience
We understand that you inherently find data easy to understand and interesting. But other people need help deriving value from numbers and charts, lessening their appreciation for your work. A different approach is to present the data in a way that everyone, not just analysts, can comprehend. Do you need to show the Design team which ads work? Don’t you dare show them data in Excel. Instead, single out the best ads and, together, discuss the differences between the two sets of ads. Likely, they’ll see things you didn’t and be more open to iterating toward better-performing ads.
5. Establish a learnings repository
Solving contradictions between insights and predetermined strategies can be complex. Ideally, research should come first when making any big decisions. Instead, often an idea is formed and implemented without doing any research at all. Your organization should have analytical leadership take a more proactive role in the decision-making process; however, this usually requires a significant shift in the cultural mindset. In the interim, start paving the way by establishing a learnings repository. Too often, valuable learnings are lost and forgotten in emails, reports, and presentations. Every business can benefit from collecting details across different campaigns, teams, and initiatives. Furthermore, looking at the larger patterns between campaigns, teams, and initiatives is essential. Does a sense of urgency always work? What about particular types of imagery? Likely no one is compiling and understanding larger learnings. Reframing one-off results into strategic and relevant “best practices” can change how your organization thinks about data and makes decisions even when you’re not there.