In Search of the Goldilocks Pre-Mover Lead

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This article originally appeared in the April 2017 Housing News Report newsletter published by ATTOM Data Solutions. For a free subscription to the award-winning Housing News Report, contact christine.stricker@attomdata.com.

Most pre-mover leads available today are either too hot or too cold.

That statement will be explored later in this article, but first a brief primer on pre-mover leads: these are leads intended to identify homeowners or tenants moving out of a home. The soon-to-move occupants are in need of a variety of services ranging from moving companies to storage facilities to home renovation (if the occupant was like Goldilocks and broke some furniture or other items in the house). They also often need to cancel or transfer a variety of services such as Internet, Cable TV and home security.

As such, pre-mover leads are of interest to many companies because they represent an opportunity to gain business — in the case of moving companies, storage facilities or home renovation — or to avoid losing business — in the case of Internet, Cable TV and home security providers.

Traditionally pre-mover leads have been generated using one of three methods, which is where the too-hot-and-too-cold discussion comes back into play.

Lots of Sizzle, Little Steak

The first two methods for generating pre-mover leads— modeled public record data and listing data — generate leads that are too hot in the sense that a high proportion are all sizzle and no steak: people who may never actually move or whose move is at some indeterminate point in the future.

The modeled leads specifically represent a list of properties that are likely to sell at some point in the near future, thus representing a potential mover. The likelihood to sell is based on an algorithm that takes into account a variety of factors that might include how long the property has been owned, how much equity the homeowner has and personal characteristics of the homeowner such as age, marital status, number and age of kids. In a typical modeled lead structure, all properties in a given market are assigned a “likelihood-to-sell” score and the top 10 percent of scores are designated as the leads.

This is all very sexy stuff, and many smart data scientists are getting much better at creating highly sophisticated predictive modeling to develop these leads. But at the end of the day, modeled leads fall short — at least as pre-mover leads; they work much better as listing leads or leads for real estate investors — because they ultimately don’t represent a person with an imminent intent to move, let alone a concrete moving date. These are folks who haven’t even made the decision to sell yet, so when they receive solicitation for moving services, it doesn’t fit their current situation or mindset.

Faulty Assumption Foundation

The second of the “too hot” leads are generated from homes listed for sale on the local multiple listing service (MLS). Not a lot of sexy data science or predictive modeling here, just a basic assumption that if someone lists a home for sale the occupants will soon be moving out of that home. The only problem is that’s not a safe assumption. Only about 55 percent of all homes listed on the MLS end up selling, according to an analysis of MLS data by Clear Capital.

Even for the 55 percent that do end up selling, the listing provides no information about when that will occur. That means companies marketing to the occupants leaving those properties are shooting at a target while blindfolded. They know the target is there; they just can’t see to nail the bullseye or anywhere close to the bullseye. Not to mention that the target isn’t even there almost half the time.

Time Travel Not Included

The third traditional method for generating pre-mover leads— sales deed data also obtained from public records data — is too cold in the sense that the lead by definition lags the actual move.

That means that once a company gets the lead it may be too late. These leads have the advantage of including a concrete moving date in the form of the closing date on the sales deed, but they are often not actionable because of the lag time involved in collecting sales deed data.

Companies interested in marketing to the occupants moving into the property can still use these public record leads somewhat effectively, but keep in mind that in many parts of the country it can take 45 days or more from the sale date to when the actual sales deed is recorded. By that time the new occupant moving in may have already secured many of the moving-related services he or she might need.

Square Peg, Round Hole

These three methods of generating pre-mover leads have been used because they have been the best available, but the truth is that none of these were originally designed as pre-mover leads — which is why they end up being either too hot or too cold for companies focused on moving-related services.

Modeled leads are really designed for real estate agents, investors and others looking to find homeowners who may be likely to sell but have not made that decision yet as evidenced by the fact that the property is not yet listed. These leads are great for agents and investors, who are offering services to help the homeowner sell the property.

The public record leads help to power some of the predictive analytics used for the modeled leads, but as a stand-alone lead they are best-suited for companies providing more long-term services for homeowners and occupants. They’re just not ideal for companies offering services specifically related to the moving process because of the time-sensitive nature of those services.

Frankly the MLS listing data really doesn’t work as a lead at all — at least for any broad application — and is simply the result of trying to fit a square peg into a round hole. That MLS listing data is being sold as a pre-mover lead at all is certainly a testament to the strong demand for leads in the marketplace and the fact that up until recently there has not been a customized pre-mover lead that is just right for those offering moving-related services.

 

A Goldilocks-Worthy Pre-Mover Lead

Realizing this gap in the lead-generation marketplace, ATTOM Data Solutions last year embarked on a quest to find a Goldilocks-worthy pre-mover lead for the industry:  one that is neither too hot nor too cold. After some extensive testing — which I’ll get to in a moment — we believe we’ve developed one that fits the bill.

This new pre-mover lead is derived from loan pre-approvals for purchases of residential real estate — an event that is in close proximity to the actual move and also includes an actual date estimated for the move in the form of a settlement date included on the pre-approval documents.

Not only is that estimated moving date provided, it’s also highly predictive, according to an extensive analysis that ATTOM conducted prior to releasing this lead product to the marketplace.  We looked at three years’ worth of historical pre-mover leads that would have been generated using this new method and matched it against sales deed data. We found that 67 percent of the leads matched to a closed sale within 30 days of the estimated settlement date included on the lead and that 75 percent matched to a closed sale date within 90 days.

Companies can now market to these pre-mover leads with a high degree of confidence, knowing that two-thirds of the current occupants they market to
will be actually moving within the next 30 days following a specific date, and 75 percent will be moving within 90 days. This data-based market intelligence provides the marketer with the tools they need to set up a targeted, time-sensitive and ultimately effective campaign.   

Please contact us if you have questions about the underlying data referenced in this article, or would like to have access to that data in the form of custom reports, API or bulk files.

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