Property Marketing Data and Insight Programmatic Advertising

Finding a home mover audience

Skyrise

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October 27, 2021 | 6 min read

The pandemic showed once and for all that when people are looking to move property it is definitively digital first

With physical estate agents closed, the digital landscape dominated, as we looked for property inspiration.

In a market where a handful of apps and sites dominate, the digital footprint of home-movers has never been easier to understand. With the ONS reporting that 11% of UK adults are moving house each year, it’s a hugely competitive market. Marketers need to understand an always changing audience, and how their competitors are performing.

Using data and insight, we work with property marketers to discover who is in-market to move from an audience pool of over 20 million mobile phone users. The information is extrapolated to give a representation of the national population. It is aggregated, anonymised data based on movement, profiles and preferences generated by 30% of the UK’s population from billions of daily network events.

The detail is in the moving data

To build a home moving audience, you need to identify users of home search apps and websites and analyse them against demographic data sets to create a profile. You can analyse the gender split, most indexing age bands, life stage, spending power, other category interests and regional distribution. This gives property marketing teams a clear depiction of their in-market users.

Catch the early mover advantage

Knowing when your existing and potential customers are planning to move home, and more importantly where they are in the moving process, is a key opportunity for both customer acquisition and retention.

Property marketers need access to agile data that allow them to identify their customers’ changing life circumstances and engage them at the best time. Generally speaking, the sooner in the user journey you’re able to identify the customer the better. Competition increases hugely further down the funnel in such a considered purchase.

Using dynamic data you can tell when and why home-movers are most in need of products and services. Using aggregated data, you can build complex audience segments such as this and then activate ads to engage them.

You can use a number of data signals to build an audience, such as location, movement and demography, however for home movers the most obvious starting place is the apps that are frequently used along with the URLs they visit. Along with general property search apps you can layer on mortgage calculator users and home finance websites. For high end property marketers the data can be analysed further to target users with high incomes.

A moving mover audience

By understanding who your audience is, and where they are located on any given day, at any given time, you have powerful actionable insight on which to plan and activate a media campaign.

This combination of contextual online data, coupled with factual offline data (such as that from Royal Mail) enables you to identify and target the c150k new movers in the UK each month. This data is updated in real-time, and covers both house sale and rental moves. With custom creative you can deliver highly targeted and relevant ads and offers to customers and prospects in-market throughout the home-mover cycle. This improves the effectiveness of your marketing, as you are able to send communications in real time at specific points of need.

By identifying where an individual is within the home-mover cycle (from pre-mover through to move homemaker) it is possible for advertisers to reach home buyers at the exact time when they need their product, in a compelling and contextually appropriate way.

Moving towards OOH Advertising

This isn’t just relevant to digital-only campaigns. With a vast data-set of 20 million people you can create true omni-channel campaigns targeting home mover markets.

By analysing movement behaviour alongside time of day and day of week, digital out of home (DOOH) advertising is a natural fit. With a deeper knowledge of when home movers will pass through certain locations, you can add behavioural analysis to physical data to better plan OOH campaigns based on the movement of people and only activating when and where you have most impact.

Targeting home movers is a hugely competitive landscape but that doesn’t mean you can’t cut through. By harnessing the power of mobile phone data you can make your marketing campaigns more effective than your competitors. At its core, you're looking to create high quality audiences of home-movers by analysing digital and real world behaviour. The datasets are highly deterministic and not reliant on panels or surveys that date very quickly. By analysing real time data of home-movers you'll know what’s happening now and not three or six months ago. This lets you build highly relevant segments that are more likely to drive performance for your advertising budget. With no reliance on cookies or unique identifiers, every audience is built under the strictest privacy controls without ever compromising personal data. All of this provides brands with very powerful insight to guide and power their home moving marketing campaigns.

Moving matters

The home-mover audience is of interest beyond just property marketers. Moving is an event which motivates people to review their existing suppliers for the home, including utilities, phone and entertainment providers, and also to shop around for new products and services. The average home-mover spends around £5,000 on move-related goods and services, and £8,000 on home improvements in the first year of moving.

Post-pandemic those figures have almost certainly increased. Anything and everything for the home is up for review from financial services and telecoms to furniture and appliances. This makes for a £7bn market, and gives a great opportunity for relevant product and service providers to serve targeted ads and offers to prospective new customers.

Working in partnership with Skyrise Intelligence our analysts turn mobile data into insights about how people behave online and offline. Find out more here.

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