It’s easy for corporate giants like Amazon and Walmart to increase the role of AI in marketing, but what about the 80% of the world’s enterprises that find it impossible to support the overhead of data science teams to power their personalization?
We get it. Using artificial intelligence in your marketing strategies to create relevant personalization is complicated. You need someone on your team who understands models and features and all of those other unfamiliar concepts.
Once you add the actual technological component to the mix, it really seems impossible to reach successful personalization. Even more concerning is the sheer amount of time it takes to analyze the data when you’re already strapped for time. Plus, you have to grapple with the logistical and bureaucratic roadblocks of bringing in a new vendor.
Who needs to add all these new things and skill sets? And who’s going to manage everything? Revenue shouldn’t be based on headcount — it should be based on how you effectively use that headcount and AI should help you rather than bog you down or give you more work to do.
To illustrate the role of AI in marketing, let’s look at an example of one company we’ve worked with. BevMo!, one of the largest alcohol retailers in the U.S., wanted to figure out how to increase its checkouts. From a marketing standpoint, however, the most the BevMo! team could do was figure out who likes wine, beer, or spirits.
The questions to ask in order to reach that segmentation are hard to pin down. There are so many options. Think about it: How do you even decide whether someone likes wine? Is it because they purchased the most SKUs in wine categories within the last year? Or is it because they bought the greatest quantities of wine?
What if Taylor purchases 10 bottles of the same wine during Thanksgiving but sticks to beer for the remainder of the year? Does this make Taylor a wine lover? That’s where things get complicated (as if they weren’t already complicated enough!).
The next thing to look at is what kind of content you give that customer. This can be a considerable challenge, especially if you have 60,000 SKUs. Does Taylor like Modelos or Stellas? Do they like rosé right now? Or petite sirah? Or both? Those are the kinds of questions marketers must ask.
It’s easy to look at an example like this and see the importance of segmentation using AI. But at the end of the day, the actual execution is very flawed — there are just so many ways to slice and dice.
When you think about doing this at scale, it probably sounds incredibly hard — and it is. There’s not enough time in the day for one person to sort through 10 million people’s wants and needs. Thankfully, AI is here to help.
To do this, we provide a turnkey enterprise-grade platform. If this sounds too good to be true, then just keep reading. We encounter skepticism all the time, so let us show you how it works.
Going back to BevMo!, they were experiencing pain points because their personalization was extremely manual. The company used a lot of different tools with a long process and few variations. As a result, the experiences they presented were either irrelevant for new shoppers or too spammy for extreme loyalists.On top of that, BevMo! was struggling with how to get started with AI-powered personalization because, like many enterprises, they don’t support a chief data officer or a chief data scientist.
In seven days — yes, only seven! — we were able to hook into the company’s SMS system and add one line of code to their web. And when we say one line, we mean one line. It’s that simple. No additional events or activity collection coding needed.
Our AI found several different ways to achieve the company’s goal. Instead of creating 10,000 rules, we gave millions of variations and decisions in just 30 days. During this time, BevMo! had more than $267,000 in sales — $50,000 of which was completely untouched by human hands thanks to our AI.
Honestly? AI is daunting, which causes many companies hesitant to use AI in their marketing strategies and personalization. But it doesn’t have to be time-consuming and complicated. You don’t need a team of data scientists to harness the power of AI; you just need the right partner and platform.
If you want to see results quickly and at scale, try Breinify out.
You have nothing to lose — and everything to gain.