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How to Target the Customers Likely to Buy Next

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AnalyticsRecently I was the honored recipient of a free week of Blue Apron meals gifted to me by a friend who appreciates my “foodiness.”  Blue Apron is perfect for a passionate cook like me because you get to experiment with new recipes and ingredients each week.

The first item on the Blue Apron Agenda was a recipe for Thai Coconut Shrimp Soup, which called for the use of lemongrass.

Now, I had never used lemongrass in my cooking before, but my friend had done her market research: she knew I was a culinary adventurist always ready to try something new (turns out lemongrass is great for infusing broth with flavor, but not so great when minced and consumed directly!). Lesson I learned is that sometimes – without proper research into a new ingredient – I do not prepare it correctly just by reading a recipe! I wish Blue Apron had provided a better way to describe the expected results of using this non-mainstream ingredient. Crunchy lemongrass in each bite of soup was disappointing. The lemongrass infused broth was delicious!

THE PROBLEM

I see a similar problem with some retailers. Some send the exact same marketing message to every one of their customers. Some customers are more loyal and have shopped many times and need to receive a different message and different offer than those who shop less frequently or not at all (never used lemongrass before).

None of us buy the same items for the same reasons. One customer orders Blue Apron recipes to try new foods, while another orders Blue Apron recipes for the convenience of having ingredients and a recipe shipped to their door.

To me, this means that you can’t send the exact same marketing message to each of your customers because each of your customers have different needs, wants, and reasons for buying.

If you don’t get to know your customers, you’ll base your marketing on what you want to sell, and not what the customer wants to buy. This type of disconnect can drastically reduce your marketing ROI and increase your marketing spend. Even worse, you’ll fail to engage the customer, whose loyalty level will remain as low as my taste for crunchy lemongrass.

THE SOLUTION

This month on the blog, I’ll focus on the three steps you can take to know your customer better, create highly targeted marketing materials, and predict which customers are likely to buy next.

I’ll outline the steps you’ll be taking in this post, and we’ll dive into each step in more depth throughout the series.

1. Adjust Your Marketing Mindset

The first thing you need to do to get inside your customer’s head is to adjust your own mindset. Some businesses believe they know what their customers want even more than their customers do.

Instead of investigating customer behaviors and digging deep into the data on hand, they assume they know all there is to know and create marketing campaigns based on the past, not the future.

Next week’s article will reveal case studies of companies that saw a huge shift in their marketing ROI simply by paying close attention to the data they had already collected on customers and by appending more data to customer records. Opening their minds to a world of previously untapped information that gave them an advantage over their competitors

2. Gather Your Ingredients

The fastest, most affordable way to predict your customer’s next purchase is to start gathering information on your customers that you do not usually collect.

Append demographic data like gender, age, income, ethnicity to each customer and use it along side the sales history of each customer to develop an informative picture of your customers and build segments of like customers.  What are the Baby Boomers buying in your store? What do the men buy? How often do affluent customers buy? Learn to speak to each segment based on their purchase history and some useful demographic data variables instead of using one-message fits all approach.  Massa & Company can append many data variables to your customer database, parse customers into meaningful segments that will inform your overall marketing strategy and show which customers will likely buy next.

3. Use What You’ve Learned

Once you’ve begun appending your data, you need to convert that data into actionable insights. After all, there’s no point in collecting and storing all of that information if you’re not going to use it to build loyalty and increase revenue.

Once you’ve gotten to know your customers in terms of demographic information, buying habits, and personal taste, Massa & Company can create a predictive model based on that information.

This model will show you which types of marketing communications will appeal to your audience segments.

For example, let’s say a particular customer segment made an appliance purchase within the past 6 months. Armed with that information, you can avoid sending them the same appliance mailing the rest of your customers are getting, and instead create a targeted campaign based on the type of item they’re most likely to buy next through predictive analytics. Someone commented on my blog in January that they bought a 100 pound safe from a retailer and that retailer keeps serving re-targeting ads to her for 100 pound safes? Why is the retailer spending money showing her pictures of what she already bought?  This doesn’t look like engagement to her it looks like a waste of money!

Just as I dove into a piping hot bowl of spicy Thai soup, I can’t wait to dive deeper into each of these three action steps over the coming weeks. In the same way that lemongrass needs the tender loving care of an experienced cook, predictive modeling needs the expertise of someone who knows exactly how each data-driven ingredient works together.

If you feel the same way about predictive analytics as I do about crunchy lemongrass, you’re in luck! All you need is the desire to predict your customer’s next purchase. Contact Bonnie at (312) 463-1050 or by clicking here now.

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About the Author:

Bonnie Massa is Founder and President of Chicago-based Massa & Company, Inc. She works with companies and nonprofits to make the best use of their information about customers, partners, donors and sponsors. With more than 30 years of experience in marketing and predictive analytics, Bonnie is passionate about helping clients make informed, data-driven decisions to increase the value of their customer base. She works with organizations of all types to attract new customers and constituents, segment existing customers and analyze customer behavior to predict future behaviors. She speaks fluent “geek” and is an effective translator between business executives and technology experts. Bonnie currently serves as President of American Marketing Association Chicago Chapter, a volunteer position leading the best marketers in the city. She strongly believes that making pasta and ice cream from scratch are worth the effort, and she spends much of her free time testing and re-testing that theory.