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Discount Less, Analyze and Test More During the Holiday Marketing Rush

Authored by ActionIQ Team

Black Friday. The phrase alone can send shivers down the retail marketing spine.

But, over time, it has transformed from a one-day, brick-and-mortar, consumer-driven shopping mania to drawn out hype and discounts weeks (and now months) ahead of time. Black Friday isn’t just a day any more–it’s an entire season. According to research from Market Track, opt-in email volume from advertisers increased 15% year-over-year between October 1 and November 19 this year.

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There’s still a lot of chatter about Black Friday numbers and that can be deceiving. Last month’s Black Friday raked in $5 billion online and that is impressive. However, it’s not just the volume–it’s the margins that count. Selling a million units is great, but what kind of impact will that really make when you’re at 60 percent discounts, free shipping, and zero (or negative?) margin.

So how do you compete when Black Friday is happening earlier and earlier and the actual holiday season seems even more focused on slashing prices? How do you identify customers earlier and organically? And without so many discounts and potentially at (gasp) purchasing full price? The answer is in the data.

There are two ways data can be helpful:

1. Identify how price-conscious each customer is. Can you separate the full-price customers from bargain-hunters? Or are you sending the same discounts to everyone, missing out on sales and leaving money on the table?

2. Personalize your messages across all channels in order to differentiate your offering beyond just price and merchandise

The challenge most retailers have is that they are not capturing the data that can enable them to execute on the two opportunities above. They have a lot of customer transaction history, but for the holidays that’s just useless. Before and during the holidays, you have a very noisy period where consumers mainly send the retailers signals through interactions, but not transactions, until it’s too late. By the time they make the purchase, it means that they’re more or less done. They made up their mind; game over.

So the first step is to move beyond just collecting and analyzing transactions. That’s great, but it will only tell you so much. Capture and analyze all interactions–such as clickstream data, data from mobile apps, and social media data–from the months (or even year) before the holidays when consumers begin their research through browsing or visiting in person. This will help you to understand when the consumer is truly looking to buy and how to best engage with them.

It’s also time to assemble your holiday SWAT team. This nimble group will be on the holiday analytics frontline to take your insights from the interaction data and quickly move it into action. This all has to happen in a matter of days–not weeks or months when it’s too late. See a micro-segment looking at a particular deal or item? Pinpoint and immediately send a message that will resonate directly (and not to an entire swath of customers who don’t care about your household goods promotion because they are interested in purchasing jewelry or cosmetics).

Finally, as you go through the new “season of Black Friday” and more months of holiday marketing, it’s important to take a lesson from the startup culture: Fail fast. Today’s marketer needs to move at higher rates of speed than ever before, and failing fast is the only way to succeed before the holidays are over! The best tactic is to adopt a “test everything culture,” so you can measure and quickly iterate and improve on new campaigns. Instead of banking on those “do or die” promotions, try out a variety of your ideas with small target groups. See the performance; glean the insights; and evolve it.

In the end, just remember: Whatever interaction data you can get—keep it all. Hoard it and ensure it is accessible beyond your IT team. Analyze, test, rinse, and repeat. With these new marketing tactics in hand, marketers can really begin to anticipate, rather than dread, the holiday season.

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