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Weathering the Storm of the Cost of Living Crisis


Amid economic challenges, sectors like retail, credit, and utilities face hardships. A plunge in spending post-pandemic paired with surging inflation triggers a consumer confidence decline. Businesses need unique strategies: smarter customer targeting for retailers, addressing increased credit needs for credit providers, and support improvements for utilities. Defensive consumer spending reduces disposable income for businesses, particularly impacting smaller enterprises. Data-driven insights at a household level enable businesses to adapt, target customers effectively, predict behaviours, and tackle unique sector challenges, assisting in crisis adaptation and future preparedness.

July 7, 2022

The retail, utilities and credit sectors are facing one of the greatest challenges of the past 40 years: As the economic situation worsens, a recession becomes more and more likely. Households feel the pressure and businesses need to adapt to survive. So, what can companies do to weather the storm and thrive during this new challenge?

The perfect storm

In a post-Covid world there were glimmers of growth, but as the world has opened back up, we’ve faced a new wave of challenges. As a result, the UK is seeing a dramatic reduction in spending. On June 24th, the Office of National Statistics (ONS) announced that the volume of goods sold in-store and online in May 2022 fell by 0.5%.

With inflation at its highest level since the 1980s, we’re experiencing all-time lows in consumer confidence. As food and energy prices continue to rise, this trend is likely to continue throughout the summer.

Some of the industries most affected by the crisis are retail, credit, and utility. Each industry faces unique challenges and in turn, will need to deliver a unique strategy in response.

  • Retail businesses will need to be smarter at customer targeting and retention to ensure a healthy flow of new shoppers while preventing the loss of existing loyal customers.
  • Credit providers must address the increased need for credit along with an increased risk of defaults or fraud.
  • Utility companies must improve their processes for supporting vulnerable customers to adhere to regulations, along with a moral duty to support these households.

Data insights and the 2022 consumer

Consumers are adopting more defensive spending behaviours to ensure they have enough money to pay for the essentials. These tactics include self-imposed checkout limits at supermarkets, reducing expenditure on luxuries, or borrowing to fund everything from clothes to food.

The change in consumer behaviour creates a reduction in disposable income for businesses in the affected sectors. With a reduction in income comes a hit to companies’ bottom lines — threatening the survival of many of them. Small businesses are particularly at risk as they lack the cash flow necessary to recover from low-income periods.

Each UK household is unique. For consumer-focused businesses, understanding each of these, whether they are an existing customer or not, will be key to success. By using data that provides detailed insight at an individual post box level, businesses can gain a true understanding of the UK consumer.

Leveraging customer data science and data modelling provides the ability to turn data into wisdom — which in turn, forms the bedrock for any business or marketing strategy through an understanding of the unique nature of each customer, and the unique issues they are facing.

Adapt. Overcome

In the current environment, identifying which UK households are most likely to be affected by the cost of living crisis helps businesses adapt to the needs of their customers. By knowing the financial status of customers at a household level, businesses get a live snapshot of current behaviours. And through modelling that live snapshot, we can then predict customers' future behaviours.

All consumer-facing businesses can use this insight to understand:

  • Who are my customers, and how are they dealing with increased living costs?
  • What is important to my customers?
  • How do I ensure my marketing messaging is effective?
  • Who should I target, and what’s the best channel to use to do it?

But this data can also help overcome unique challenges within each sector.

For Retail, this insight can identify which physical store locations might face the most amount of pressure from reduced takings. Those located in the most hard-hit locations are likely to see a reduction in foot traffic and profits. Using data science, retailers can implement strategies ahead of time to address the issue, such as stocking cheaper products, creating targeted promotions or advertisements, or even reducing the number of physical stores.

Credit agencies and lenders can use the data to pinpoint households that are more likely to default. This goes beyond the process of deciding on whether to extend credit or not at the point of sale. It can identify households that already have credit, but now have a propensity to default. To better support those that face financial hardship as well as to manage credit risk.

The same is also the case for Utility providers. The current energy crisis has put an increased regulatory burden on providers. Our analysis has identified 5,055,359 vulnerable households out of the circa 30 million in the UK by modelling features beyond simple financial flags. Each one of those is considered a financially vulnerable household that they are obliged to actively provide additional support.

Data science at a household level can help consumer-facing businesses adapt and overcome the challenges that lay ahead. Through understanding where consumers are at this moment in time, and where they might be in six months, we can identify behaviours and keep your business ahead of the curve.

How can Outra help my business?


News & Insights

The latest industry news, interviews, technologies, and resources.
8 read

How HUX’s ROAS reached new heights with Outra’s lookalike targeting

HUX Health, an e-commerce supplements brand, partnered with Outra to enhance its marketing efficiency using precision lookalike targeting. In just three months, HUX saw a 146% increase in ROAS), a 60% decrease in CPA, and a 32% increase in purchase volume. Outra’s unique data-driven approach enabled HUX to target the right customers more effectively, significantly improving their marketing performance despite geo-targeting restrictions on Meta and Google.

Read More
June 10, 2024

Launched in 2022, HUX creates the best tasting health supplements using expertly blended and scientifically proven ingredients. HUX is an aspirational brand marketing predominantly on Meta and Google.

The challenge:

In the first eighteen months HUX was averaging a return on ad spend (ROAS) of below 1 and a cost per acquisition (CPA) of £55. To really thrive the way HUX users thrive, the founders had to improve these metrics. But at the same time Meta and Google were introducing more restrictions on geo targeting making it harder to manage ad spend. As experienced entrepreneurs, the HUX team knew they had to be innovative and take a different approach to get ahead of the competition.

Outra has a unique data set that allows for precision targeting of customers. It feels like an unfair advantage
- Damien Byrne, EVP, HUX

The solution:

Outra approach targeting from a unique angle. Our machine learning goes far beyond how Google Analytics uses data like age and location. Rather than analyse individual personal data, our algorithms analyse a host of household data like financial status and lifestyle preferences. Outra AI dives deep into the interactions of 2600 data points for every household in the UK which enables us to predict their behaviour and generate a product specific score for over 30 million UK residential addresses. The house someone lives in tells us a great deal about their lifestyle aspirations. 

In this way we create lookalike profiles that are GDPR compliant. They also circumvent the Meta and Google restrictions so we can create target postcode districts and long-lat disks with a high density of prospects.

Creating a lookalike profile for HUX

The first stage in creating a lookalike profile for HUX was to ingest all the household data about their existing clients. Then we trained our machine learning model to give each household a HUX score and create the lookalike profile of the top scoring households. 

Before working with Outra, the HUX team thought their target market was mainly hipsters in their twenties. But when we crunched the data it turned out most of their customers were slightly older, more affluent and better educated. Their customers tended to be a lot more interested in the ingredients and the science of the products, rather than just the look and feel of the brand. 

Giving HUX cost effective UK wide reach

Using Outra’s data, the HUX team were able to target lookalike households all over the UK and spot patterns in their locations. For instance the Outra model even revealed that many of the customers lived near parks, perhaps because more affluent people live near open spaces and also have the opportunity to exercise more often. 

The results:

After three months using Outra data, HUX achieved:

  • 32% increase in Purchase volume
  • 47% reduction in spend
  • 60% decrease in Cost Per Acquisition
  • 146% increase in Return On Ad Spend

The Benefits:

One of the big benefits of the Outra data was that HUX could use it across all of its marketing channels. There is no division between what works best for PPC and what works best for paid social. 

Outra unified the channel audiences and ensured they were consistent
- Damien Byrne, EVP, HUX

We also worked closely with the HUX activation team enabling competitor analysis and AB testing on messaging. This resulted in HUX narrowing down activity to five high performing ads. They were also able to refine customer flows through the funnel and steadily upsell to increase the average order value. 

Outra works with many different types of clients and our data scientists create a lookalike profile, or customer centric propensity model for each one. For startups the aim is to enable the acquisition of customers with speed and efficiency often against very tight metrics. For larger established companies, the aim may be to identify and buy media with higher attribution rates. We are comfortable working with all the marketing stakeholders, including our clients’ tech and data departments, people and existing activation agencies.

Often a client will ask their agency to use our data. The agency can be reluctant, but once they see the results, they want to white label it so they can offer it to their other customers.
- Lucinda Edwards, Head of Growth, Outra

Case study
8 read

Heylo slashes cost of leads for shared ownership with Outra's Propensity to Buy audience targeting

Heylo, a leading shared ownership provider, partnered with Outra to implement their Propensity to Buy audience targeting. This integration drastically reduced Heylo's cost per lead from £15 to £3, increased applications by 129%, and boosted high-quality leads by 43%. Outra's data-driven approach allowed for precise targeting on Meta and Google, overcoming recent geo-targeting restrictions and optimising marketing efficiency.

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June 10, 2024

Established in 2014, <span style="color: #00C79F; font-weight: bold;">heylo's</span> Shared Ownership solutions bring owning a home within reach for millions of previously excluded buyers. <span style="color: #00C79F; font-weight: bold;">heylo</span> has become one of the UK’s leading shared ownership providers, and works in partnership with national, regional and local housebuilders, and wider stakeholders to deliver affordable homes. <span style="color: #00C79F; font-weight: bold;">heylo</span> operates under two brand names:

With interest rates currently so high, there is a growing demand for affordable homes. But as <span style="color: #00C79F; font-weight: bold;">heylo's</span> Marketing Director Dan Jones points out, in property the margins are always tight:

We have a small marketing budget, so we have to make it work effectively
- Dan Jones, Marketing Director, heylo

The Challenge: targeting effectively on Meta and Google

<span style="color: #00C79F; font-weight: bold;">heylo</span>
predominantly markets on Meta (Facebook and Instagram) and Google (PPC). Ideally they want to target people who live close to the specific property and would be interested in shared ownership. But this has become a lot harder due to recent restrictions on geo targeting. 

The Meta targeting restrictions have made the cost per lead rise significantly

<span style="color: #00C79F; font-weight: bold;">heylo's</span> ethos is to make owning a home affordable to previously excluded buyers, and would never discriminate. But as Dan Jones says <span style="color: #233DFF; font-weight: bold;">“pounds aren’t being spent where they should be spent”</span>  and digital marketing agencies don’t have solutions to overcome these restrictions.

The solution: Outra’s Propensity to Buy, fine tuned for shared ownership.

Outra are the only people in the UK that have this property data, and are able to activate it so effectively

Last year <span style="color: #00C79F; font-weight: bold;">heylo</span> started using Outra’s Propensity to Buy solution and the results were startling. For instance in the four months previous to using Outra, the average cost per application to Your Home was £15. Less than two months after integrating Outra data into their digital acquisition marketing, that average was down to £4. 

That is a 74% drop in the cost per application. Overall Your Home saw a 129% increase in applications and a 43% increase in high quality leads. Outra were able to do this by positioning Meta’s 17km disks precisely over high intent areas for shared ownership.

Since we started using the Outra UK wide informed radii placements, we have seen a record level of applications at an all-time low cost.

Outra’s Propensity to Buy models

Outra’s Propensity to Buy solution analyses and scores every household within a set radius of the property being marketed. This means <span style="color: #00C79F; font-weight: bold;">Heylo</span> can create GDPR compliant custom audiences that remove the restrictions of the Meta disk altogether.  

There are three core components to the score:

  • Product fit - a set of machine learning models that predict how likely each household is to be interested in a specific bedroom count, property type and property style. 
  • Readiness to move - a model that considers how long people have lived in their current house and life events that would trigger a house move.
  • Affordability - This model takes account of the household income and equity to calculate if they can afford the property.

The scoring models are built with "Privacy by Design", and are based on household-level data rather than personal data. In other words Outra target households rather than individuals and is therefore GDPR compliant.

As Carolin Sievers, Lead Data Scientist at Outra says, there's a load of data going into the models. <span style="color: #233DFF; font-weight: bold;">“We use almost 200 features from our datasets to inform the model. For instance the current attributes of the property they live in, how long they've lived there for, their demographic data and lifestyle choices.”</span>

Outra’s ability to focus on people interested in shared ownership

The key differentiator for <span style="color: #00C79F; font-weight: bold;">Heylo</span> is that Outra has fine-tuned their model specifically to identify people that fit the profile of someone that would be interested in shared ownership. 

The benefits: Scaleable and focused programmatic marketing

A big part of Dan Jones’ job is getting the right recipe for <span style="color: #00C79F; font-weight: bold;">Heylo's</span> digital acquisition marketing. Being able to live-ramp Outra data into their Meta and Google channels with custom segments that can go down to postcode level, enables them to target clusters of high intent customers. Dan can also use broader keywords cost effectively because he has been able to zone into locations using 1km disks rather than Meta’s 17km disks. 

The fact that Outra’s data models are proprietary means they can be optimised for each client’s needs. They score each household so even specific letterboxes can be targeted for direct mail campaigns. 

I love working with a partner who really is on the same page and knows what my priorities are
Case study
Logo of upstix
8 read

How Pre Mover Transformed UPSTIX iBuyer Acquisition Strategy

Upstix Case Study for Pre Mover‍: “Moving house is such a fundamental trigger point for so many suppliers. Pre Mover gives us an edge that others don’t have”

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March 15, 2024
“Moving house is such a fundamental trigger point for so many suppliers. Pre Mover gives us an edge that others don’t have”

Upstix, a leading house iBuyer in the UK, provides people with a new way to sell their home. But as a disruptive start-up, the biggest challenge for COO Frederick Jones is identifying and marketing to people who are actively planning to sell their house.

Using the Pre Mover AI tool from Outra enables Upstix to not only target who is about to put their house on the market, but also to focus on the segment of those most likely to use an iBuyer. 

The challenge: Identifying and engaging people actively planning to sell their houses

The most valuable consumer group in the UK are home-movers. They spend more before, during and after their move than any other consumer segment. 

For Upstix to survive in a very competitive market, Frederick has to be able to maximise the return on his marketing investment by successfully targeting people who are actively planning to sell their house. “My challenge is to originate actionable leads in a very cost-effective way. We just can’t afford to spray and pray.”

On average homeowners spend £13,000 within a year of moving on expenses like renovations, furniture and electronics. 

The solution: Pre Mover has a proven 1 in 4 success rate of identifying people selling their house in the next 6 months. 

Precise Segmentation

Outra have trained Pre Mover to not only identify the people in the UK planning to sell their house, but also to focus on the people most likely to use an iBuyer. Pre Mover uses 2,300 data points and 130 signals to identify people who are looking for a quick sale, potentially due to probate or financial distress, and that have the type of property Upstix can sell on quickly. “Pre Mover gives us the base level of home-movers, and then we can apply various other layers on top of that around individuals in the household and the type of property, so we're able to precisely segment the type of person and specific location of houses on streets.”

No matter what segment of the home-movers your company targets, Pre Mover can be configured to find them. 

Continual optimisation

A key part of the partnership between Outra and Upstix is the continual optimisation of the tool. “We do a 360 degree refresh every three months and we evaluate the success of every campaign to improve the machine learning. This segmentation analysis feeds into where we target our social media and direct mail spend, and the look-alike audience for email campaigns. It is an iterative process so we can constantly improve and retarget our marketing with Pre Mover.”

Machine learning within Pre Mover means that the longer it focuses on a segment, the more precise it gets, and so results continually improve. 

Sales and marketing integration

Frederick also sees the benefits along the whole sales funnel. “It’s not just about targeting people initially, but also about how they go through sales and actually become clients. The whole sales funnel is continually fine tuned from top to bottom.”

90% of Upstix’s leads come from targeted advertising. This means that Frederick’s team isn't waiting for people to find them by chance as they search online. Upstix are proactively approaching the right people at the right time. What is more, the successful conversion rate on these leads is 12% which is four times the industry average.

“When leads come in, our sales team is spending time speaking to people who understand our service, and are in a position to sell. So we are having much more impactful conversations”.

The benefits: Evidence that your marketing is delivering return on investment 

“A lot of companies promise better data analytics and more leads, but most don’t deliver”

Real estate DNA

A big factor that gives Frederick confidence in Pre Mover is that real estate is in Outra’s DNA. Outra’s founders have decades of real estate experience and a deep understanding of what data is meaningful and informative. 

Fail-safe accuracy

The other big reason why Frederick believes in Pre Mover, is that there is a fail-safe way to check its accuracy. “If Pre Mover predicts a house move, say 98 Elscott Road, we can check on The Land Registry six months later, and see if that property actually has changed ownership”. This gives us a definitive score-card for Pre Mover, and a sure-fire way of optimising checking its accuracy.” 

“To see the success of the model makes me feel really confident. It gives us an edge, and makes me believe the business will be a success”

Case study
The Art of Targeted Advertising with Home Mover AI
8 read

The Art of Targeted Advertising with Home Mover AI

Maximise ROI with Home Mover AI's Precision Timing in Advertising

Tait Lawson
Marketing Director
Read More
April 1, 2024

In the intricate dance of advertising, timing is not just a factor—it's the central stage. Home Mover AI has revolutionised this aspect, bringing an unprecedented level of precision to targeted advertising. By tapping into the predictive power of Home Mover data, advertisers can now reach potential customers exactly when they are most likely to make key decisions; significantly boosting the effectiveness of marketing campaigns.

Section 1: Applying Home Mover Insights Across Industries to Reinvent Marketing ROI

Elevating Marketing Strategies with Predictive Accuracy

The Home Mover product from Outra, with its advanced AI and predictive analytics, offers an innovative approach to enhancing marketing ROI. By accurately predicting when individuals are planning to move homes, this tool enables advertisers across various industries to time their campaigns to this critical decision-making phase. This precise targeting ensures that marketing messages are not just relevant, but also delivered at the most opportune moment.

Real-World Impact Across Diverse Sectors

For instance, a furniture retailer can utilise Home Mover data to identify prospective customers who are in the process of moving, offering them timely deals on home furnishings. Similarly, a telecom provider can target households moving to new areas with special broadband and TV package offers. These targeted approaches ensure higher engagement rates, thereby leading to improved conversion rates and maximised sales efficiency.

Section 2: Innovative Use Cases Across Industries that Benefit from Home Mover Insights

Versatility of Home Mover Data in Targeted Advertising

The application of Home Mover data is not limited to a single industry; its benefits span across numerous sectors. This predictive tool can be used by companies in fields ranging from home entertainment to personal finance, each leveraging data to meet their specific advertising needs.

Precision in Campaign Execution

The strength of Home Mover lies in its ability to offer high-intent consumer targeting. For instance, an insurance company can utilise this data to identify households that are relocating to new home, and might be in need of home insurance products. This level of precise targeting enables businesses to not only reach the right audience but also to do so at a time when their products are most needed, thereby significantly enhancing campaign success and ROI.

Section 3: How Home Mover Data Has Become King of Targeted Success with Predictive Marketing in the Digital Age

The Evolution of Digital Advertising

Amidst the rapidly evolving digital advertising landscape, predictive marketing has taken centre stage. The ability to forecast consumer behaviour and preferences has become increasingly vital for marketing success. Home Mover data, with its rich predictive insights, emerges as a critical asset in this new era, enabling advertisers to craft campaigns that are not just reactive, but proactively aligned with consumer needs.

Home Mover as a Cornerstone in Predictive Marketing

Home Mover's data stands out as a key player within this transformative period. It provides advertisers with a powerful lens in which to view potential customer transitions, particularly in the context of moving homes. This insight proves crucial, as a home move often triggers a series of purchasing decisions. By tapping into this data, marketers can anticipate needs and offer solutions before the consumer actively seeks them out, thereby positioning their brands strategically in the customer's journey.

Shaping the Future of Marketing Strategies

The predictive power of Home Mover data is reshaping how marketing strategies are formulated. Instead of a scattergun approach, advertisers can now employ precise, data-driven strategies to target consumers. This shift not only improves the relevance and effectiveness of advertising campaigns but also enhances the overall consumer experience, as messages and offers are more likely to align with the consumer’s current life stage and needs.

Section 4: Anticipating Consumer Behaviour By Leveraging Data for Effective Campaigns

Harnessing Predictive Insights for Timely Engagement

The core strength of Home Mover data resides in its ability to anticipate consumer behaviour with remarkable accuracy. This predictive insight is invaluable for advertisers aiming to engage with their audience at the most opportune moments. Understanding when consumers are likely to make significant life changes, such as moving homes, allows for the crafting of campaigns that are not only relevant but also exceptionally timely.

Strategic Campaign Planning with Home Mover Data

By leveraging Home Mover insights, advertisers can strategically plan their campaigns to coincide with these key decision-making periods in consumers’ lives. This could involve targeting individuals with offers for home-related services and products, or providing timely information that assists them during the moving process. Such targeted and well-timed advertising not only improves campaign performance, but also enhances customer experience, leading to stronger brand loyalty and long-term engagement.

Section 5: Future-Proofing Marketing Strategies with Home Mover AI

Adapting to a Changing Marketing Landscape

As the marketing world continues to evolve, staying ahead of the curve becomes increasingly important. Home Mover AI is an essential tool in this respect, offering a forward-looking approach to predictive marketing. By understanding and anticipating the shifts in consumer lifestyle and behaviour, advertisers can future-proof their strategies, ensuring relevance and impact in a consistently evolving market.

The Continuous Evolution of Targeted Advertising

The integration of AI and data analytics in marketing is not a fleeting trend but a fundamental shift. Home Mover data is at the forefront of this shift, continually refining the way advertisers approach campaign planning and execution. Its role in the future of marketing is not merely about targeting the right audience but also about fostering a more intuitive and responsive advertising ecosystem.


The art of targeted advertising in the digital age has been significantly enhanced by the advent of predictive tools like Home Mover AI. This innovative approach has revolutionised the way advertisers plan and execute their campaigns, ensuring that they reach consumers precisely when they are most receptive. The predictive power of Home Mover data has not only redefined marketing ROI but also established a new standard for customer engagement and satisfaction. As the marketing landscape continues to evolve,the strategic use of such AI-driven insights will undoubtedly play a pivotal role in shaping the future of targeted advertising, making timing not just a factor, but the essence of successful marketing strategies.

Predictive Home Mover Marketing How Any Industry Can Benefit
8 read

Predictive Home Mover Marketing How Any Industry Can Benefit

Discover the power of predictive Home Mover marketing to boost ROI across diverse sectors

Tait Lawson
Marketing Director
Read More
March 25, 2024

In the fast-evolving world of marketing, the ability to anticipate consumer needs and behaviours is a coveted advantage. Enter the realm of predictive marketing, a technique that leverages data to foresee consumer actions. At the forefront of this revolution is Home Mover data, a tool that, while closely associated with real estate, holds untapped potential for a myriad of industries. This article delves into the versatility of Home Mover data, exploring how it can serve as a linchpin in understanding consumer intentions and reshaping marketing strategies across various sectors.

Section 1: Anticipating Consumer Behaviour by Leveraging Data for Effective Campaigns

The Importance of Consumer Insights

In today’s data-driven marketing landscape, understanding consumer behaviour is not just beneficial; it's essential. Home Mover data provides a window into the minds of consumers before they make significant life changes. This home mover information is invaluable, as it gives marketers in any industry a head start in tailoring their strategies to meet the evolving needs of their audience.

Shaping Advertising Strategies

The ability to anticipate when a consumer is planning to move can revolutionise advertising campaigns. For instance, retailers can target pre-movers with promotions on home furnishings, while automotive companies might highlight family-friendly vehicles. This foresight allows for a more strategic, targeted approach, ensuring that marketing efforts are not only seen, but are also relevant and compelling.

Section 2: Personalised Marketing for Any Business by Crafting Tailored Ads with Home Mover Data

The Era of Personalisation in Advertising

Personalised marketing has become the cornerstone of successful advertising campaigns. In an age where consumers are bombarded with generic advertisements, the ability to stand out with tailored messaging is invaluable. Home Mover presents a unique opportunity to personalise advertising efforts based on imminent life changes.

Creating Customised Ad Experiences

By leveraging Home Mover's predictive data, businesses across various industries can craft ads that directly address the needs and preferences of home movers. For example, a telecommunications company can offer special broadband packages to individuals moving to a new area, or a pet supply company can target pet owners moving to a property with more outdoor space. Such customisation not only enhances the relevance of the ads but also significantly boosts consumer engagement.

Section 3: Applying Home Mover Insights Across Industries To Reinvent Marketing ROI

Transformative Impact on Marketing Returns

The utilisation of Home Mover data has been shown to revolutionise the return on investment (ROI) in marketing campaigns across diverse sectors. By targeting consumers at a time when they are most receptive to certain products and services, businesses can achieve higher conversion rates and better returns on their marketing spend.

Case Studies and Examples

Consider the case of a home improvement retailer that utilised Home Mover data to target individuals planning to move. By offering tailored promotions and services, the retailer witnessed a significant uptick in sales and customer engagement. Similarly, a financial services company leveraged this data to offer home insurance and mortgage products to potential movers, resulting in a higher uptick of their services and an improved ROI.


Home Mover data transcends its traditional real estate confines, proving to be a versatile and powerful tool in the realm of predictive marketing. Its ability to provide insights into consumer behaviour and intentions before a major life event like moving house, is invaluable for marketers across various industries. By enabling personalised advertising and enhancing marketing ROI, this data not only meets the current demands of a data-driven advertising world but also sets the stage for future innovation. As businesses continue to seek more targeted and effective marketing strategies, the role of predictive analytics, especially in the form of tools like Home Mover, is set to become increasingly pivotal.

Insurance Home Mover Shield To Safeguard Revenue
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The Home Mover Shield To Safeguard Revenue in Insurance

Home Mover lifecycle insights and AI is crucial to the insurtech stack to safeguard revenue and customer value

Read More
March 18, 2024

In the fiercely competitive landscape of the insurance industry, the ability to protect and grow revenue streams is paramount. Senior decision-makers and C-suite executives are constantly on the lookout for innovative strategies that align with this objective. Understanding the Home Mover lifecycle through the power of data and AI offer a unique advantage by predicting customer household moves, thereby enabling insurers to make timely strategic adjustments. This foresight not only retains revenue but also minimises potential disruptions in the customer journey.

The Home Mover Strategy for Insurers To Maximise Customer Lifetime Value

The Essence of Customer Lifetime Value
In the realm of insurance, understanding and maximising customer lifetime value (CLV) is crucial for sustained success. CLV represents the total worth of a customer to a business over the entirety of their relationship. For insurers, this means not just selling a policy, but nurturing a long-term relationship that evolves with the customer’s changing needs.

Leveraging Home Mover Insights
Gaining deep insights through data and technology into when and why customers are likely to move homes, insurers can tailor their services to accompany customers through different life stages. Whether it’s adjusting coverage when a customer moves to a bigger home or offering additional policies relevant to new life circumstances, these targeted services significantly enhance CLV.

Unleashing Home Mover Data for Diverse Insurance Product Cross-Selling Power

The Strategic Advantage of Cross-Selling
In insurance, cross-selling is not merely a sales tactic; it's a strategic approach to deepen customer relationships and enhance revenue. By offering customers additional, relevant products, insurers can address a broader range of customer needs, reinforcing their role as comprehensive service providers.

Utilising Home Mover Insights for Effective Cross-Selling
Predicting when a customer is about to move through home mover lifecycle data and AI plays a crucial role here. When a customer is in the process of moving homes, their insurance needs invariably change. This transitional phase presents an opportune moment for insurers to cross-sell various insurance products - from property insurance to contents insurance. By aligning these offerings with the specific circumstances of the home move, insurers ensure relevance, which is key to successful cross-selling.

Tailoring Upsell Strategies Using Home Mover Predictive Insights

Upselling as a Revenue Growth Lever
Upselling, the practice of encouraging customers to purchase more coverage adding products, upgrades, or other add-ons, is a powerful tool for revenue growth in insurance. It goes beyond mere transactional sales; it's about providing customers with value-added services that genuinely enhance their coverage.

The Role of Predictive Insights in Upselling
Home Mover lifecycle data insights and the power of AI is becoming invaluable within the insurtech stack. These insights enable insurers to identify moments when customers might be most receptive to upselling. For instance, if the data indicates a customer is moving to a high-value property, it’s an opportune time to suggest premium insurance packages or additional coverage options. Tailoring upselling strategies in this manner ensures that offerings are not only timely but also highly relevant to the customer's current needs and lifestyle changes.

Retention Reinvented With Home Mover Insights To Secure Insurance Customer Loyalty

Enhancing Retention through Personalised Interactions
In insurance, retaining a customer is often more cost-effective than acquiring a new one. Home Mover insights offer a robust solution to the retention challenge by enabling highly personalised customer interactions. By understanding when customers are likely to move, insurers can proactively offer relevant services and support, demonstrating attentiveness to the customer's life changes.

Building Loyalty with Continuous Value Delivery
Loyalty in the insurance sector is fostered not just through competitive pricing but, more importantly, through continuous value delivery. Home Mover insights enable insurers to stay one step ahead, anticipating customer needs and offering solutions before the customer even recognises the need themselves. This proactive approach builds a strong sense of trust and reliability, essential components of customer loyalty.

Future-Proofing Insurance Revenue with AI

Anticipating Customer Behaviour Shifts with AI
The future of insurance revenue lies in the ability to anticipate and adapt to customer behaviour shifts. AI and predictive analytics, as exemplified by Home Mover, are key to this adaptability. By harnessing these insights, insurers can not only protect existing revenue streams but also identify new growth opportunities.

Adapting Strategies for Sustained Growth
The dynamic nature of AI-driven insights allows insurance companies to continuously refine their strategies in line with evolving customer preferences and market conditions. This agility is crucial for not just surviving but thriving in the rapidly changing insurance landscape. Home Mover lifecycle insights combined with AI and technology represents a significant step in this direction, offering a tangible way for insurers to future-proof their revenue streams.

Empowering Modern Insurers to Safeguard Revenue and Customer Value

Outra's Home Mover emerges as a pivotal tool in the strategic arsenal of modern insurance companies, particularly in the quest to safeguard and grow revenue. By maximising customer lifetime value, enabling effective cross-selling and upselling, and enhancing customer retention, this tool represents a comprehensive solution to several key challenges facing insurers today. Moreover, the integration of AI and predictive analytics signals a broader shift in the industry towards more adaptive, customer-centric models. As senior decision-makers and C-suite executives navigate this evolving landscape, tools like Home Mover are not just advantageous; they are essential for future-proofing revenue in a world where understanding and anticipating customer needs is paramount.


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