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HomeBlogBlogTurning Data Into Dollars: How to use Predictive Analytics to Increase Revenue and Decrease Marketing Costs

Turning Data Into Dollars: How to use Predictive Analytics to Increase Revenue and Decrease Marketing Costs

Bonnie Massa_January Blog Post 3In my last post, I revealed how Predictive Analytics can be used to predict customer behavior in the same way that a great recipe can predict a delectable meal.

Just as a well-thought out recipe can predict mouth-watering culinary creations (I’m currently on an Italian kick!), a well-thought out, data-driven marketing plan can be used to increase your company’s revenue and significantly decrease marketing costs.

Here’s how:

Find Out Exactly What Your Customers Want (without asking them!)

By using Predictive Analytics, you can find out exactly what your customers want simply by looking at their data-based behavior.

Predictive Analytics uses data to determine why customers do what they do, when they are most likely to make a purchase, and how you can position your company to fulfill their ever-changing needs.

If you can accurately predict what your customers want, you won’t waste time or money guessing. You will only invest in marketing strategies that promise predictable outcomes, and in turn, drastically increase revenue and slash marketing costs.

Streamline Your Email Marketing

Predictive Analytics can reduce marketing costs both online and offline.

Take email marketing, for example. Many companies waste time, energy, and precious resources on email campaigns that don’t work.

Why don’t they work?

Because the email strategies being used are not based on data.

Effective, strategic email campaigns use past customer behavior to predict future outcomes.

By analyzing how a customer has responded to your past email campaigns, you can create follow-up sequences specifically tailored to their purchasing behavior.

You can also cut marketing costs and increase engagement by segmenting email lists and only emailing those customers most likely to respond to a particular campaign.

Decrease Direct Mail Costs

Many companies practice a ‘set it and forget it’ mentality when it comes to direct response marketing. If you have a direct mail budget and a mailing list, you may be tempted to send mailings to everyone on that list every single time.

Stop!

By using Predictive Analytics, you can accurately predict which customer segments will be most likely to respond to mailings, and skip those least likely to buy based on this marketing method.

Not only will you use a drastic reduction in the cost of direct mailings; you’ll be able to refocus your energies on marketing strategies that do resonate with each specific customer segment.

You don’t need every single ingredient in your refrigerator to make mouth-watering minestrone, so why waste precious dollars marketing to every single customer in your database?

With Predictive Analytics, you can simultaneously increase revenue and decrease marketing costs by accurately predicting exactly what your customers want, when they want it. Instead of wasting money marketing to every customer every time, you’ll be able to create offers for segments that are ready to buy right now.

And the only thing more delicious than a perfectly primed customer is a piping hot bowl of Italian wedding soup, or maybe my homemade Tiramisu.

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 40 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 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.


0 thoughts on “Turning Data Into Dollars: How to use Predictive Analytics to Increase Revenue and Decrease Marketing Costs

  1. I love reading your blogs. Your information is attuned to my work with nonprofit organizations in terms of garnering funds from individual and major donors. Yours is an informative and helpful read.

  2. Great post Bonnie. What data points are most important in predicting future behavior? I’m thinking it varies greatly by product. I see big companies get it wrong. Staples serves up pay-per-click ads based on what I bought, but they don’t seem to segment that data. I bought a huge 100 lb safe a year ago and I am still being served ads from Staples about safes. They must think I buy lots of safes all the time and need to stay stocked up! Staples is hurting themselves by showing me that they don’t really understand what they are selling or what I want at all.

  3. Hi Lisa – Thank you for the example of Staples re-targeting you inappropriately. Yes, the most important data points are subjective to the product/industry as well as to the marketing tactic being used (online ads, email, direct mail, etc.). Predictive Analytics is a not a ‘set it and forget it’ tool – it should be dynamic. It should be tweaked often based on results! Since you bought a big ol’ safe I’d target you with items that are ancillary to having a safe. At the very least, target you with items bought by other people who bought that safe!

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