Speedeon built response models for a regional furniture brand’s pre-mover and new mover direct mail and email program. After mailing only the top-scoring model deciles, pre-movers showed the bigger gain, a 2.2% lift in response and a $75 spend increase. New movers responded 0.4% better and spent $83 more.
If you’ve heard of Speedeon, then you know we know a thing or two about new mover data and marketing. It’s our thing. If you haven’t heard of us, well, we work with some of the largest financial, insurance, D2C, and retail brands in the US, helping them leverage new mover triggers to enhance their acquisition and retention programs.
We’ve spent years building and refining our new mover database. You can access an accurate and verified United States new movers database through Speedeon, which identifies about 30 million movers a year and refreshes its records daily.
The strategies enabled by our new mover data also run the spectrum: customer acquisition, cross-sell and services upsell strategies, win-back, and reducing churn. We’ve been around the block more than once and have the new mover playbook to prove it.
This post is the first of a series where we show you different new mover strategies deployed by our clients. We will also share insider tips on leveraging this data to serve those moving into a new home. When the right strategy and the right data come together, good things happen.
Why New Mover Marketing Works for Furniture Retailers
Movers are a big audience. About 11.8% of people in the US moved to a different home in 2024, according to the Census Bureau’s American Community Survey, the most recent annual count available. A new home usually means new furniture, so movers are a natural fit for a furniture retailer.
New mover marketing for furniture retailers targets households in the weeks before and after a move, when spending on the home peaks. In Speedeon’s 2026 State of Mover Spending Report, 61% of movers spent at least $1,000 above their normal budget around the move, and household goods were the most common unexpected expense.
In this post, we highlight a regional furniture brand that wanted to be more relevant to consumers who lived within its footprint.
The retailer realized they needed to be more competitive in an incredibly saturated market. To gain a competitive edge, they looked to Speedeon to help them leverage pre-mover and new mover data. Happy reading!
Download our guide to new mover marketing here
The Client: A Regional Furniture Brand
Our client is a regional furniture brand we support by providing turnkey new mover direct marketing programs. The program targets two groups of movers with direct mail and email communications: pre-movers in contract and new movers. Both groups are further segmented based on household income and home value.
How We Built the Response Models
Modeled new mover database of US movers by Speedeon combines multi-source signals, such as utility and phone connects, and change-of-address and subscription updates, to track and predict household relocations ahead of or immediately following a move.
While our client has been pleased with overall program results, we identified additional opportunities to improve program performance by modeling responders to the program. By using historical response data from previous campaigns, our data science team trained response models, one for each mover type. This process included:
- Enriching the responder records with geo-demographics.
- Applying machine learning algorithms to identify key attributes among the two groups that predict the likelihood of responding to a targeted mover message.
The modeling development process analyzed how features like dwelling type, household composition, debt management, home value, and population density (urban, suburban, or rural) impacted responders vs. non-responders.
Scoring Movers and Selecting Deciles
Once the model was built, it was used to score which movers were most likely to engage with the brand after receiving direct mail and/or email. The highest-scoring movers were selected by model decile. Deciles split the scored audience into 10 equal groups and are commonly used to simplify the selection process. Lower-scoring deciles were divested to optimize the marketing spend with minimal impact on response.
The Results: Modeled Mover Data Lifted Response and Spend
The outcome? In market, the models performed.
New mover data on its own performs well for many brands, but with modeling, it’s a game changer. It’s marrying intent and likelihood of responding. Most providers can supply the trigger. Speedeon adds the analytics that push campaign performance further.
As one client who was running a new mover program at a competitor said, “It was generally ok, but we could tell it wasn’t their thing. We can tell this is your thing.”
Frequently Asked Questions
What is the difference between pre-mover and new mover data?
Pre-mover data identifies households that are about to move, such as homes listed for sale or under contract. New mover data identifies households that have recently settled at a new address. In this campaign, the furniture brand reached pre-movers in contract and new movers, with a separate model for each group.
How does response modeling improve a new mover campaign?
A response model scores each mover on how likely they are to respond, based on the traits of past responders. The brand can then mail the top-scoring deciles and drop the rest, which cuts spend without giving up much response.
What data went into the models in this case study?
Historical campaign response data, enriched with geo-demographics. The models weighed dwelling type, household composition, debt management, home value, and population density.
Ready to Get More From Your Mover Program?
Contact us if you’re looking to improve or get into life-event marketing. Our team can help you build a mover program and measure what it’s doing for your brand.
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