At Subscription Show 2021, Kyle Fohlin, VP of New Business Development for Wiland, Emma Nicoletti, VP of Predictive Client Solutions Department for Wiland, and Stephanie Taylor, SVP of Acquisitions for Belardi Wong, discussed how subscription businesses can utilize first-party data, third-party data and data co-ops to acquire customers.

Data: it’s the currency all subscription businesses must use to stay relevant, acquire new customers, and retain current customers. But not all data and the way it is acquired are the same. First- and third-party data are only part of the picture; data collaborations and co-ops are crucial to acquiring new customers and keeping them.

Through acquisition modeling — predictive models, which are used to acquire new customers or consumers to the brand — businesses can reach more customers. Instead of shaping marketing efforts around what may work, companies can directly target their best customers, the customers they want, or customers they didn’t even know existed. All of this is done through the collection, management, use, and collaboration of data.

First-Party Data

“Understanding your data is the first part of this journey,” says Kyle Fohlin, VP of New Business Development for Wiland. “We talk about customer journey all the time, but I like to think about it as a data journey.”

Many subscription businesses and consumers are familiar with the term “third-party data.” It’s been in the news and appears in many pop-up disclaimers on websites. But there is an important distinction between first- and third-party data.

“First-party data is anything your customers gave you that you get to keep and use as much as you want,” says Emma Nicoletti, VP of Predictive Client Solutions Department for Wiland.

It’s a simple but important difference. Transactional data comes from customers, information like how much they spent, names, and contact information. That data, once voluntarily shared by the customer, belongs to the company. Usage data, when collected by the company itself, is another great example of first-party data.

“My big line is: Keep absolutely everything because…there’s no such thing as too much [of first-party data],” says Nicoletti.

Anything from the time of day a customer signs up to how long between they opened a link and put in their credit card — all of that data can become predictive at a later date. Keeping as much information as possible helps with segmentation once enough data is available.

“We sometimes find with our clients that if you don’t know what to collect, just collect everything,” says Stephanie Taylor, SVP of Acquisitions for Bolardi Wong.

This is particularly important for prospects who just converted/new buyers because that’s when they’re the most excited to be working with the company. They’re going to offer up more information than they usually would. Pieces of data like name, billing address, shipping address, if the purchase is a gift, the number of children in the household, gender, and location can be difficult to capture at a later date. At that point, many businesses will then have to utilize third-party.

Fohlin, Nicoletti, and Taylor, all agree businesses need to focus on getting the most out of first-party data. The more first-party data businesses can collect on their customers, the easier it becomes to segment and discover other, similar customers.

“When we talk about personas or segmentations, what we mean is your customers are not one single group of people,” says Nicoletti. “When you think about segmentation, you can do age and demographics and how they interact with you. Or you can think about their value to you.”

Though customers of a business all have the common trait of shopping with the company, there are many differentiating factors between them. Not only are there demographic considerations, but how people buy, the frequency of purchases, the ideal customers, and the customers that aren’t a big loss if they never return again. For subscription businesses, first-party data is more unique because there are different layers. For example, one-month, three-month, six-month or annual subscriptions indicate different types of buyers. Through enough data collection, expansion opportunities begin to emerge.

Third-Party Data

“Third-party data is any piece of information you have about your customers that didn’t come from them,” says Nicoletti.

If a company collects additional information on a customer from another source like location, marital status and number of people in the household, all of that is considered third-party data. The next step to understanding data is to work with a third-party data provider who can add additional elements a company may not be able to capture as first-party data. Not only is third-party data information, but it can also be layered on to validate the data that a company already possesses.

“You’re coming at [data collection] from a different angle and seeing how this person is behaving when they’re not talking to you,” says Nicoletti.

Third-party data is about gaining a fuller understanding of a customer outside of their interactions with a single company. Third-party data providers indicate how much money a client spends everywhere else and what percentage a single company takes from their wallet.

Third parties can also offer more information so a company can contact a customer in a different way (i.e., you have the email address, but you want to physically mail them something). Even gaining a birth date (without the year) can allow for triggered mailings to wish them a happy birthday, which can encourage additional spending.

What’s interesting about third-party data is there are so many vendors who can offer that data to companies. It’s significant that Salesforce in the 2021 State of Marketing Report noted the average data provider usage for the companies that responded was 12. So they’re using 12 data partners for third-party data and aspire to go to 15 in 2022.

“I think that’s one of the best practices — to work with a number of highly vetted, qualified data partners that can get you the information that you need,” says Fohlin.

They also asked companies why third-party data is so important and 40% said they were completely satisfied with the completeness of their data. This indicates they’re looking to fill in the pieces that are missing from their first-party data.

Data Collaboration and Co-ops

Where can companies start with ethically gaining third-party data? Through data collaboration and co-ops sometimes called second-party data. Data collaboration or co-op is taking first-party data from two or more parties and sharing it on a private basis to the benefit of both parties.

“One of the most important parts of a data co-op is that its blind. For example, at Wiland, we have approximately 4,500 companies from around the country, and they give us all of their data: name, address, transactional history, what you bought, and when you bought it. None of those companies know who the other companies are, and there is no option to purchase data directly,” says Nicoletti.

In another example, Netflix can’t contact a reputable co-op and ask for Disney+’s customer list. However, Netflix can offer up their data and ask the co-op to build them a customer acquisition model, based on all the data from the entire base of customers in the co-op. The best co-ops are blind, secure, and have a large number of participants so one contributor doesn’t overweigh a certain category. And it’s a best practice to work with several co-ops for model methodology reasons.

“With multiple co-ops, it all comes down to is bias. If you think about only shopping at your neighborhood grocery store, you might not even know that other products exist. And your customer list can be the same way. If you keep acquiring customers from the same general pool, from the same collaborative database, for example, you can miss expansion opportunities that another source would provide. Additionally, when you bring in that data from other sources, then that first source starts to get broader. So all of the collaborative data sources are improved by clients using at least a couple [co-ops],” says Nicoletti.

A company “knows what they know” about a customer because of first-party data. But when a company works with a co-op, they get to see what other companies know about a customer. It’s at this point that many companies realize their customer is not just their customer. There are a lot of insights that can be gleaned from their spending habits.

There are, of course, different modeling solutions that co-ops offer. Some may look at lifetime value, some may look at top of funnel, some may look at response rates, and some may model for return on ad spend. The model doesn’t have to be built for the best prospect; it just needs to be properly delivered. Though co-ops started 30 years ago in the direct-mail world, they’re morphing into becoming the digital data provider on which models are based.

With these definitions of the different types of data in mind and how they’re utilized by co-ops, it’s clear that subscription businesses need to tap into these resources to acquire more customers.

• Step 1: collect as much information from customers as possible.

• Step 2: begin to consider how third-party data can validate or expand the current insight on the customer base.

• Step 3: look into several different data co-ops that will offer customer base expansion opportunities through shared data with other companies. 

In part two of this two-part series, we’ll look at the science behind the predictive data models and how companies like Wiland build these models to effectively capture new customers for companies.