Inboxes are only getting more cluttered and new features such as tabs in Gmail make engagement yet a higher priority than it already was. It’s time to get real…meaning real in your customer’s eyes. And the only way to do that is with advanced segmentation.
What separates advanced email segmentation from basic? More use of more data in more ways.
If your business is like most, you’re collecting data left and right. The challenge lies in putting that data to use, and that’s what is required in order to do advanced segmentation. These days, despite all of the technological advances and ways to capture data, “behavioral data still remains…‘the greatest untapped marketing asset.’”
In order to be that relevant to each customer on an individual basis, you need to constantly be collecting data. But you also need that data actionable, and therein lies the key to behavioral marketing: After you collect it, you need to put it to use, by getting that data back into your system in a way you can analyze and react to.
How to tap into your untapped marketing asset
Your data is your marketing asset…or even your marketing arsenal. Today relevance means something other than using a customer’s first name in an email. It means delivering the content that matters to that customer at the time that it matters to the customer. If you have 5,000 or 55,000 or even 555,000 people in your database, that adds up to a lot of individual preferences to be taking into account. That is the data you should be collecting, analyzing and utilizing, and you can only do that using advanced segmentation.
The limitations of basic segmentation
Basic segmentation is typically your demographic data, the kind of information normally stored within your email service provider’s platform. It’s usually in a flat file data, and therein lies your limitation: In a flat data file, every time you want to add new data, you have to add a field.
Basic segmentation is fine if your marketing messages are tailored to factors like gender and ZIP code. But what if you want to track individual customer orders so you can create more targeted messaging? For example, say you’re a restaurant and you want to track the menu items customers order so you can target your future marketing to them accordingly. Every time a customer comes into your restaurant for a meal, you have to add a field to your flat file database….every single time.
That not only quickly becomes cumbersome, but you end up with a lot of dead space too because you’ll have many empty fields. Not every customer visits your restaurant three times per week. Some might only come in three times every year, and those customers will have dozens of empty data fields as a result.
Why advanced email segmentation requires a relational database
The relational database was invented to solve this problem. Rather than add your restaurant order data to your email data, you create a table to track orders only and then relate that data to that customer. You essentially “hook” the tables together so you can both collect deep data on a single customer and dig into that data to market to that customer.
Marketers in food industry that look to grade their email game need to update their data game. Like Cameron Kane from iPost says in his restaurant email marketing strategy guide, segmentation is one of the most important pieces of the puzzle.
This is not only behavioral data like click data from your website, but includes all the transactional information. The adage says that people vote with their feet, or in this case with what they eat.
The more data you can collect on each customer, the more relevant your marketing can be. The more relevant your marketing, the higher your ROI.
Just consider one overly simplified example: When you have a few customers who buy big ticket items only occasionally, a few customers who buy cheap items frequently, and a few customers who buy big ticket items frequently, these are all three very distinct customer types. With a relational database, you can know who is who, and with advanced segmentation, they can all get different messaging that’s appropriate to the kind of buyer they are. You wouldn’t want to market the big ticket items to the smaller budget customers, nor would you want to push a lot of frequent selling onto the occasional customer.
Or go back to the restaurant analogy for a specific example: If you know a customer buys a nice bottle of wine every time he is in your establishment, you can market specifically to him when you have a wine-tasting event coming up. You risk offending your teetotalers, on the other hand, if you market a wine-tasting event to them.
Compare that scenario to a restaurant collecting business cards in a fishbowl. All that restaurant manager knows is Sue Smith was in his restaurant. Period. The only marketing he can do to her is to say, “Come back to my restaurant.” That’s hardly a targeted message, and hardly one to get noticed in today’s cluttered inbox.
A relational database collects the data in a usable format. Advanced email segmentation makes the data useful. But none of this is possible if you don’t have the best email service provider for the job.
Will your current ESP fit the bill?
In order to achieve this kind of advanced segmentation, you’ll need to lean heavily on your email service provider. But first you need to ask: Is this kind of advanced segmentation doable with your current email service provider? Maybe, if their data structure is built on a relational database. Probably not if they use a flat file data structure.
Advanced segmentation is the way to the extreme relevance customers want and expect. It should be part of your email technology roadmap. But it might mean a new ESP is in order to make it happen.