It is amazing how many large companies talk about how they are boosting their efforts to capture the attention of millennials: 'We need to tap into the millennials' and 'How can we improve our brand to target millennials more effectively'.

Please �" stop chasing millennials, instead, use data to drive marketing.

Sure, the Millenials generation is the biggest cohort in history �" representing 32.5% of the US population. Focusing your marketing efforts using a blanket approach to consumers in this group is pointless when you have access to powerful tools which can turbo-charge marketing results.

Here’s why:

It’s like saying �" we’re only going to sending marketing material to people with brown hair. Everyone’s talking about customers with brown hair having more disposable income, and these digital nomads are ‘mobile first’, and… and…

Newsflash: Within this age segment of the population are millions of sub-sets and micro-groups which, while they may fit the age profile of your latest marketing campaign �" they will have nothing else in common with other millennials.

The fact is �" millennials are unique, and even if you don’t think they are �" THEY believe that they are special. To effective communicate to this audience, you need to break down the segment into smaller bite-sized pieces, into groups which are hyper-tailored to their specific interests and behavioral patterns.

How do we target millennials?

As an established business, you have access to rich and powerful data sources which should be your immediate GO-TO for any marketing campaign. Who are your best customers to date? Do you know the real LTV of a customer? Which customers buy nothing, but are influential over other customers? What drives each segment to purchase? Who drives them to purchase?

With these questions in mind, it’s time to stop listening to anyone who has a vested interest in spending your marketing dollars (I’m looking at you �" media buying agencies). JPMorgan Chase recently cut the number of websites their media displayed on from 400,000 down to 5,000 websites and saw almost no drop in performance.

Audience segmentation is your guiding light. Follow it.

Here are three basic ways you can get started with segmenting your audience.

1) Demographic segmentation

The most basic of targeting capabilities, segmentation by anything more than age (aka millennials). I wrote a detailed explanation of how to segment loyalty program member databases. Start there if you’re new.

2) Propensity-based scoring

Fundamentally PBS is the ability to predict the chances, or likelihood of a particular customer engaging in a specific activity; based on the statistical history of other customers who have previously engaged in the same activity. These are typically used to predict the percentage change a user will interact with whatever particular activity you can dream up.

This is a little more difficult as it requires some basic machine learning knowledge to implement, but once you get going, the results can be incredibly powerful as your analytical team runs multiple ML models, creating greater accuracy.

3) Perfect customer analytics

Similar to propensity-based values scoring, in perfect customer analytics, you’ll want to use a simple analytics visualization tool like ZoomData to import success transactions. Data visualization packages will let you see similarities and traits between your most high-value customers. Perhaps a large segment of your customers who spend over $200 are buying on mobile, or they’re purchasing after 11 pm, or perhaps, even they’re transacting within the first 5 minutes of visiting your store.

There are many variables to play with and cross-reference to identify patterns and customer traits to pinpoint your perfect customer. The goal is to drill down deeply as possible until you have very specific criteria.

If I ask you- “Who is your best customer? Describe them”, and you answer “Millenials.” Chances are �" your boss is getting ready to “re-accomodate” you �" United Airlines style.

Understanding and implementing the framework which drives true data-driven decision making for marketing isn’t a fast process, but rest assured that once your process is well defined; every marketing dollar invested will ultimately result in more successful transactions.

Mark Ross-Smith
Mark is chief data editor and travel industry big data expert focusing on airlines, hotels and loyalty programs. Mark has worked with many travel companies to help them connect the dots between big data, commercial innovation and revenue. Mark contributes regularly to 4Hoteliers.com

www.traveldatadaily.com