All too often, when asked how a marketing campaign performed, the analyst pulls a report with pre-configured metrics and sends it to the requestor with a comment like “The conversion rate was 9.8%, above the target of 7%”.
Job complete? Sure, a task was completed, but the analyst didn’t truly analyze.
So what’s missing? Actual analysis.
When looking at the data pulled, to be truly valuable, the analyst should unlock their inner 3-year old, and ask “Why?”
Now, we don’t mean ask, “Why is the sky blue?” Ask:
- Why is conversion X%? Why isn’t it higher? Why is it that high?
- Why didn’t we meet our target (if below target)?
- Why did we exceed our target (if above target)?
Why is asking “Why?” so important?
Because being an analyst is a journey. One campaign leads to another.
If an analyst wants to be valued, they should provide insights. Help the person who asked, “How’d the campaign do?” answer their unasked “So what?”
- So what should I spend next time?
- So are there customer groups that converted at a higher or lower rate?
- So did all geographies perform equally?
- So which ad types worked the best?
How can one know what “so what” questions they’re going to ask?
Well, ideally they would have asked a few good questions before they started pulling data for a campaign. An analyst should understand what the campaign levers are, what the customer focus was and why the campaign was running in the first place.
If an analyst can’t get good answers to their good questions, they can try backing up to a higher level and ask a few “So what” questions of their own like,
- Help me understand how this campaign supports the results your business unit is expected to deliver this quarter?
- What customer segments are you focusing on for success?
- So what might you do next?
Asking good questions leads to finding out what matters.
- Finding out what matters provides business context for the situation data is being pulled
- Business context makes ‘doing analytics’ much easier. The Analyst will be able to drill down, segment and analyze aspects that are relevant to their organization (check out more discussion in this earlier post about how to make web analytics easier).
Let’s rewind. Rather than “The conversion rate was 9.8%, above the target of 7%”, isn’t the following more useful?
“The overall conversion rate was 9.8%, above the target of 7%. We analyzed whether this higher than expected conversion rate was broad-based. It was not. Display ad visitors who came from DailyPlanet.com had a clickthrough rate of 2.1% and converted at 4.3%, while DailyNews.com ads had a clickthrough rate of 0.7% and converted at 24%. We suggest finding out from the adserving company what content on DailyNews.com led to this remarkable conversion. Perhaps a niche campaign on similar content could be tried next.
By delivering insights rather than just pulling data, an analyst will be doing their job, demonstrating real (higher) value and potentially positioning themself for a promotion.
If you’re pulling data and not providing insights, unleash your inner 3-year old and ask “Why?” and “So What?”
We’d love to hear if this works for you.