How to increase marketing reach using lookalike modeling

Reaching the right customers on the right channel is a tall order these days, especially with the rapid rise of omnichannel behavior. Instead of finding your business and product/service offerings on a single marketing channel, your prospects are spread far and wide.

Fortunately, your business can use what we term “predictive audiences” to filter out all of the noise and find the most valuable prospects across all of your marketing channels. This is done by using lookalike modeling to discover users who most closely match your best customers based on prior behavior.

Segmenting your target audience in this way allows you to increase engagement, boost conversions, and get the most out of your marketing efforts.

In this guide, we’re going to show you how you can increase your marketing reach by using lookalike modeling to find customers most likely to purchase your products and services. If your business wants to stay ahead of the competition, incorporating new segmentation methods and targeting techniques is the way to go.

What is Lookalike Modeling?

Lookalike modeling is a segmentation technique that allows your business to find prospective customers most likely to engage with your company and make a purchase.

When your business already has customer data including lifetime value, total purchases, entry date, and a variety of other customer-centric information, you can use this data to create predictive audiences that match your existing customers’ “profile.”

To make this process as simple as possible, platforms like Lytics have added lookalike modeling functionality to their platforms, letting your business quickly build a complex model that incorporates hundreds of customer data points to filter out only your most valuable prospects.

When your marketing team starts using lookalike modeling in addition to your existing segmentation strategies, you could see excellent results.

Using lookalike modeling to reach more prospective customers

Using lookalike modeling can be a gamechanger for marketing teams, saving both time and money in the long run. Instead of manually segmenting your prospects based on what they’ve purchased in the past and when they’ve bought, the entire lookalike modeling process is automatic.

All you have to do is feed your customer data into the lookalike modeling system, and it’ll generate a predictive audience for you to target.

In the next few sections, we’ll walk through the predictive modeling process, and how a lookalike model can generate extremely relevant customer segments quickly, easily, and efficiently.

Segment based on unique customer characteristics

The “bread and butter” of lookalike modeling is to segment a predictive audience based on their unique customer characteristics.

What are the common threads and similarities between customers who have purchased your high-ticket products? What behaviors do these customers share? What customers, out of all of the prospects we’re filtering, share these same characteristics or behaviors?

Once the lookalike modeling algorithm matches prospects who most closely match past purchasers or high-value clients, it’ll return a list of potential matches for your marketing team to take action on.

Analyze all known information to extrapolate commonalities & trends

After matching customer behaviors and common characteristics, a lookalike model has the ability to make connections a human couldn’t make in a reasonable amount of time.

As an example, consider a prospective customer who is interested in listening to a certain genre of music, and as a result, is far more likely to purchase one of your products. If this data is available in your customer database, the lookalike modeling system will be able to use it to make that connection.

Even seemingly irrelevant data can be the key to pinpoint targeting.

Cross-check features based on seasonality

Some of your customers will only buy certain products based on seasonality, but the connections a lookalike system can make goes far beyond the obvious.

Marketing your winter products to customers who always purchase “winter gear”, for example, is an obvious connection your marketing team can make. Using lookalike modeling, however, the most subtle purchasing patterns can be picked up on, even if the product itself isn’t seasonal.

Your lookalike model may uncover the fact that a certain type of customer typically purchases your product in the spring, while a different customer profile buys in the winter. Your marketing team would never be able to make such a subtle connection based on logic alone.

Generate a predictive audience model

Once all of your data has been analyzed in detail, the output of lookalike modeling is a list of target customers who are most likely to purchase your products or services.

Your marketing team can then take this data and begin a new campaign to draw them in and make new sales. By using a platform that has already incorporated lookalike modeling into its core offering, you’ll be able to discover a wide range of use cases that can help grow your business and boost revenues.

Use Lytics to increase your marketing reach today

If you’d like to expand your company’s marketing reach through the use of lookalike modeling, contact Lytics today to learn more.

We’ll work with you to determine how your business can take advantage of lookalike modeling to reach your most relevant prospects as quickly and efficiently as possible.