Why Red Isn’t Bad

As professionals, we always aspire for success. As marketers, we always aspire to be in the 'black'. But negative uplift is one of the most essential tools for a marketer’s success. Here's why

Posted in , , on 25 July 2019 by:

It’s hard to argue against the benefits of incrementality testing. Not only is it the most accurate method of deducing the actual cost of acquired users, but it can also prevent you from cannibalizing your organic traffic. The process provides valuable insight into your marketing spend and allows you to achieve an important goal for all CRM managers.

As we’ve reached mid-2019, it seems like incrementality—the added revenue generated by a campaign—is no longer just a buzzword. Most marketers already understand that measurement is the ultimate proof; we should embrace it and then celebrate those green numbers.

Experiments don’t always report good news, though. The truth is, these insights, that could be considered bad, are sometimes even more valuable than pointing out which activities are working.

Not so long ago, a lack of technology forced companies to rely on consulting companies to measure and analyze their marketing activities. Consultants often found themselves in the uncomfortable position of having to explain that the product wasn’t great, sales efforts were failing, or their marketing was meh. To avoid a ‘shoot the messenger’ scenario, consultants needed excellent business communication skills.

Today, marketers can invest in technologies that leverage Test and Control groups to automatically measure a campaign’s incrementality, eliminating the need for such a messenger. Expertly and strategically flagging ineffective campaigns is essential for marketers, and fits in perfectly with Optimove's scientific approach.

So what does red indicate?

A credible positive uplift means that the campaign was effective, successfully influencing customers towards desirable behaviors. Similarly, a credible negative uplift means that the campaign was detrimental, driving customers into undesirable behaviors. Naturally, for lower-is-better types of metrics (such as churn rate, cancellation rate and return rate), the opposite conclusions hold.

If you encounter a campaign with red figures, it actually means that the Control group is outperforming the Test group, you should actually feel lucky to find it! You may have just stumbled on a campaign that drives your customers away, meaning that you may want to take a deeper look into it.

Now for those tips I promised:

  1. Stop ineffective campaigns

 When a campaign is running for a while without significant results, I suggest you stop your campaign and put your efforts elsewhere.

If for example, both the test and control groups respond the same way, the campaign isn’t effective. Basically, your customers are indifferent to receiving the campaign you are sending out. In this case, it’s best to stop the campaign, regroup, and try something else. For example, say you offer customers a 10% discount and both test and control groups respond to it the same way. In this scenario, you’re offering a discount for no reason and ultimately crippling your revenue. If I may allow myself to do some small blunt self-promotion, Optimove’s AI-bot autonomously brings these insights to marketers’ attention.

  2. Choose the better option

If you like to run A/B tests, you probably know not all campaigns are created equal. Hopefully, one campaign treatment will outperform the other, allowing you to optimize your marketing efforts. When running an A/B test, if one treatment is performing better than the other and some people responded significantly better to the one action over the other, you should continue sending only the winning action.

  3. Or better yet, move to Self-Optimizing Campaigns

Don’t pay the cost of generalization. Maybe treatment A—an enticing promotion—is better for most of your customers, but treatment B—a heartwarming message—is better for others. Why force one group to receive the option they prefer the least. Self-optimization engines, like the one inside Optimove, won’t change the action for the entire audience, but send the most relevant one to each subsegment of your audience. As a result, using self-optimizing campaigns means dropping the losing action for each subsegment, in a way that allows marketers to forgo generalization.

 4. Trim your audience to include only a sub-segment that responds to the given action

The final way you can deal with red campaigns is by taking a deeper look into your segments. It might be that a subsegment is reacting positively to your campaign, but is outshone by the larger, indifferent majority. For example, in the below screenshot, 14% of the segment is responsible for most of the uplift. Armed with this insight you would probably be best served by splitting the audience in two. Keep the same campaign for the responding 14% and create a new campaign to try out on the remaining 86%.

Remember that realizing your campaign isn’t working is just as important as realizing it’s working, maybe more so, because when it comes to a bad campaign, you’re either losing or leaving money on the table. Ultimately, losing campaigns present an opportunity to grow if acted on correctly. Take action into your own hands and follow the above tips so you’re no longer left waiting for the “messenger.”

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