Over the last couple of weeks, we have shared the first six steps that retailers need to follow to ensure their digital channels are optimized correctly.
From understanding your initial objectives to ensuring you are researching and testing as part of the process, we’ve explained it all. And the final part of our step-by-step guide ties all of this information up to make sure you get the most out of your digital channels.
Step 7: analyze the early data
Start by analyzing the data available for the campaign, both in the platform itself and through your tracking. This will likely vary by the channels you are using and the amount of tracking available. I always try to look at the data for several key optimization triggers before making any changes to the campaign, as knee-jerk optimizations can damage a campaign.
Personally, I like to look at the audiences we are targeting first; are they all behaving in a similar way, or are there particular audiences bringing up or down the average performance for the campaign? Are the audiences too big so we’re spending money too quickly without any results? Or too small so they are struggling to serve?
Then I look at creative and messaging, which is why a proper testing plan is so important. If you only have one ad, how will you know which message or visuals drive the most action from your audience? How are users engaging with creative A v creative B? Which version of the copy is getting more users to convert? How does this compare to copy on other channels?
Once I have a good idea of the role both audiences and creatives are playing in performance, I will start to delve deeper into the more granular optimization triggers such as time of day, placements, device or demographic breakdowns. By the end of step seven you should have a list of all the optimization triggers that you would like to change.
Step 8: prioritize
Only then, when I’ve seen the data that tells me what is and isn’t working across the whole campaign, will I prioritize the changes I want to make. With too few changes money is being wasted, but too many too quickly and the campaign struggles to understand which direction you are pushing it in, leading to a longer learning period.
Prioritize getting smaller changes done quickly, a couple at a time. If an optimization will force your campaign to undergo its learning period again, use this opportunity to make one or two other big changes. Completely changing a campaign (for example, swapping out all creatives or audiences) will be like going back to the start of the campaign, so keep that in mind when you are analyzing your results.
Step 9: replace, don’t reduce
In the early stages of a campaign, optimization should be more about replacing than reducing. For example, a week into your programmatic campaign you find that your ‘30% off select ranges’ creative is driving a weaker ROI than your ‘Sale now on’ creative. As you are still early into your campaign, switching off the ‘30% off’ messaging means you’d only have one creative version left live. Instead you should take learnings from previous campaigns or other channels and find an alternative for the ‘30% off’ creative. Keep all three creatives live until they have gone beyond their learning period, and only then optimize down to the two best performers.
Reducing too much too soon is especially damaging when optimizing audiences. Pausing all but the best-performing audiences will massively reduce the reach of your activity. There are a finite number of users available to reach and an even smaller amount who will convert, so reducing your activity down to only the best too early into a campaign will dry up the converter pool, leading to weaker performance later down the line.
Step 9.5: funnel budget
Running alongside your replacement of weaker performing optimization triggers, you should also be looking to funnel your campaign-level budget into the stronger performing triggers. Put higher bids or more budget against the strong converters whilst still feeding your tests enough budget to see if your replacements have worked. Circling back to step four, if you have given too much control over to the platform, funneling budget becomes much harder.
Step 10: trim the fat
Replacing weaker optimization triggers can only be done for so long – at some point you will have to start switching things off. By far the easiest optimization to make is moving budget from a weak-performing audience/campaign/channel into one that is already performing well. This point comes back round to the need for sharing results between teams, channel agnosticism and budget fluidity during the optimization process.
Step 11: repeat steps 7 to 10
Continue to analyze the data, prioritize your optimizations and replace your weaker performing optimization triggers. Once you’re sure that no replacements will beat your best performing optimization triggers, trim the fat. Depending on the length of the activity this step can be done once or a hundred times. The important thing is that it is regularly done.
Step 12: wash up
Often overlooked once one campaign finishes and another begins, ‘washing up’ a campaign’s performance will mean you can easily replicate the successes of the campaign. The first question when washing up should be “did this activity achieve its objective?” and from there you can analyze performance by optimization triggers and come up with key takeaways that should be shared across the digital channels.
To summarize, optimizing digital channels isn’t just switching off any activity that doesn’t make lots of sales. Retailers must put the leg work in before campaigns even go live to ensure they properly understand what their campaigns are trying to achieve, what good looks like and how they are going to consistently improve performance as time goes on. Optimization should be based on data and quantifiable results, which means it is not always a quick fix – instead relying on testing, waiting, analyzing and testing again.
If you want to discuss how best to optimize across your digital channels, get in touch with the expert team at Summit today on firstname.lastname@example.org.
Laurence Cresswell is paid media product manager at Summit Media.