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Will you be A/B testing on Black Friday?

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Last year, despite the pandemic, Black Friday grossed $14.13 billion in online sales, an 18% increase from 2019 online sales ($11.9 billion).
This year, we’re pleased to continue running experiments during the Black Friday period for all of our eCommerce clients this year.
Our Chief Experience Officer, Chris Gibbins, shares his thoughts on testing during Black Friday:

“I’m really pleased that the Creative CX team are continuing to run online experiments during the Black Friday period for all of our eCommerce clients this year. Users are hard to predict at the best of times, let alone during the frenzy of a sale. So in my mind it’s even more important to A/B test and learn what’s really working during these periods. What marketing and sales messages, creative treatments, imagery etc. are resonating best with your would-be customers? The “code-freeze” shouldn’t mean a freeze on learning IMHO.

“Yes there can be challenges depending on the traffic levels and also the particular nature of the experience being experimented with. E.g. if a low traffic, low conversion website there could be challenges in detecting any differences between variations during the short period of a sale. And then if you do find a winning variation during that sale period you might have to wait another year before you can benefit from that learning i.e. next years’ Black Friday event.

“If you want to maximise sales actually during the Black Friday event, that’s where Multi-Armed Bandit (MAB) approaches become interesting. For those who haven’t used this approach, MAB’s use optimisation algorithm’s to divert more traffic to ‘potentially’ winning variations, reducing overall losses and maximising conversions of the primary metric.

“I’ve also been reminded again in these last few weeks about how experimentation can really empower the various client teams involved, including those responsible for coming up with the ideal Black Friday marketing approaches.

“I love how the various teams we’ve been working with have started to really embrace A/B/n testing…. And especially the “n” part of that. How they’ve started to enjoy the creative freedom of testing more than one variation, to push themselves. Whoever said that being data-driven restricted creativity?

“Without the safety-net of A/B testing so many creative ideas would never see the light of day.”

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