Thirstie is a technology company that offers an end-to-end solution for the alcohol industry, connecting brands with consumers through an integrated e-commerce platform. Their services include regulatory compliance, delivery logistics, and data analytics to streamline the online sale and delivery of alcoholic beverages.

## Challenge: Pioneering direct channel consumer data for the alcohol industry

E-commerce has revolutionized the way alcohol brands reach their consumers, offering a direct sales channel that bypasses traditional distribution models.

This direct relationship unlocks the most valuable data asset for a brand, a list of end customers. Prior to the emergence of an e-commerce channel for alcohol, alcohol beverage brands' customer insights were limited to the data they could garner from their distributors and retail sales data.

Recognizing the opportunity within this order data lie, Thirstie set out to make consumer insights a central component of their service offering. Their goal was to go beyond mere transaction data, providing brands with deep, actionable insights into a given brands’ customer base.

## Obstacle: Going beyond transaction data with predictions

While Thirstie had ample transaction data, they lacked any additional data on these buyers. Thirstie’s ability to deliver customer insights meant they would need access to 3rd party consumer data and the analytical resources to make sense of it all.

Challenge one, was licensing and reconciling thousands of transactions with a large consumer database would be both expensive and complex, involving substantial investment in ETL and computing power.

Challenge two, was identifying meaningful patterns and trends consistently and at scale.

## Why Faraday: Plug and play persona analytics

Facing a long development cycle in a competitive market, Thirstie looked to Faraday as an infrastructure provider who could not only handle data enrichment and ETL, but also the modeling workload to derive insights from this combined dataset. With access to Faraday’s Identity Graph, Thirstie only needed an email address associated with an online transaction to tap into hundreds of data points on every customer in their database. The consumer data covered the full spectrum of demographic, financial and psychographic data, ensuring a complete view of each brand's customers could be built.

With this combination of transaction and consumer data, Thirstie used Faraday’s k-means clustering models to produce customer persona sets by alcohol beverage type.

Each time a transaction was observed, Thirstie used Faraday to assign each buyer to the appropriate persona, populating this information automatically in their data warehouse. Instead of building a bespoke solution, Thirstie could link Faraday’s consumer data with their warehouse, ensuring data is refreshed daily.

Thirstie displayed these personas in an analytics dashboard in their product, providing its clients with a rich understanding of the distinct socio-demographic segments within their customer base.

Thirstie also made this data available at the order level, so that their clients could leverage it for personalized engagement and advertising..

## Results: A Faraday powered core offering reduces Thirstie’s sales cycle by 30%

By partnering with Faraday, Thirstie was able to quickly bring deep insights and customer personas to its users, on scalable infrastructure. They did this without having to increase their expenditures on data science resources or the licensing of third party data assets.

Since partnering with Faraday in 2020, Thirstie has seen its client base more than quintuple, and the length of its sales cycle has dropped by 30%.

In May of 2024, Thirstie was acquired by Cocktail Courier.

Thirstie, an e-commerce platform for beverage brands, built a new analytics feature, powered by  Faraday, that drove adoption.

How e-commerce platform Thirstie reduced their sales cycle by 30% with an analytics feature powered by Faraday

Buying a new house while selling your current one is a colossal headache — and a massive financial burden. You’re fixing up your place for the sale and prepping to move, scouring new neighborhoods and going to showings, not to mention finagling your finances to make the transition work while your equity is still tied up in your current house.

[Orchard](https://orchard.com/) is a technology-driven real estate company that’s leading the charge for a simpler, stress-free way to buy and sell a home. With Orchard, you can unlock the equity in your current home to buy and move into your dream home before you sell. Plus, they offer a host of innovative tools to assist you every step of the way, from finding and closing on the new place to prepping, listing, and marketing your current one.

There’s no question that Orchard is an invaluable resource for home buyers and sellers. But they operate in just eleven specific markets, including Atlanta, Denver, and Houston, and that hyperlocal focus posed a unique set of challenges for Orchard’s marketing team in their early years.
We recently sat down with Graham Lesko, Senior Manager, Growth Marketing at Orchard, to chat about those challenges and how Orchard teamed up with Faraday to solve them.

## Getting local marketing right is tricky with Facebook Ads

Like many DTC brands, Orchard relies heavily on Facebook for top-of-funnel marketing. But when they came to Faraday, they were struggling to run targeted campaigns. Since they’re a real estate company, they face extra limitations in Facebook right off the bat in order to comply with fair housing and lending laws.

On top of that, Facebook’s native lookalike capabilities couldn’t handle the granular geographic targeting Orchard needed. “We got so narrow that any of the audience tools that these platforms offer off the shelf, like lookalike audiences or interest audiences, really weren’t that valuable for us,” Lesko explains. “We were forced to go broad within those [regions].”

With broad audiences, Facebook’s algorithm managed to deliver a decent volume of leads, but lead quality was poor. Just a small percentage became mid- and lower-funnel opportunities.

**The problem was clear:** they didn’t have the kind of data they needed to power more sophisticated targeting efforts. Without that data, they couldn’t reliably reach their ideal leads.

Orchard looked into a number of solutions, including contracting with third-party data vendors and working with Orchard’s data science team to leverage that extra layer of data in Facebook.
Ultimately, they chose to work with Faraday, taking advantage of our [responsibly-sourced identity graph](https://faraday.ai/features/data) and proven [predictive models](https://faraday.ai/features/predictions) to build the audiences they needed at a fraction of the cost of building their own AI pipeline.

## Reaching the right home buyers and sellers

Faraday started by building a machine learning model to identify people most likely to become Orchard customers. Since all our models are powered by our own identity graph, which contains consumer profile data on every US adult, it surfaces people that Facebook’s algorithms might overlook. Orchard’s audience was then uploaded to Facebook via direct integration.

By building a custom audience from scratch, Orchard was able to target just the most promising home buyers and sellers. They could finally focus on the audience that was likely to deliver the most value, and the difference was immediately noticeable.

“We’re driving higher intent users who really are looking to move,” Lesko says, “and not just get a valuation on their house.”

How much higher is that intent? Well, Orchard has seen a 30% lower customer acquisition cost with Faraday audiences compared to their original broad audiences. When it comes to ad spend efficiency, that’s a no-brainer.

## Improving attribution around iOS 14

When we asked Lesko if last year’s iOS updates and Facebook’s resulting attribution issues have changed how he thinks about his Facebook strategy, he told us it’s going to continue to play a dominant role in his channel mix.

“They give us the option to be hyperlocal in a way that a lot of other channels don’t,” he says. Running a campaign in specific regions is not something they can do, for instance, on podcasts, which are another important channel for his team.

“I would love to be able to diversify more, but until we’re a more national brand we’re going to be reliant on Facebook for the long term. So having a company like Faraday… is really huge for us.”

## Buy and sell your home with Orchard

We love working with Orchard — and so do thousands of happy homeowners and first-time buyers around the country, who appreciate the flexibility Orchard provides in the buying process and the extra certainty on the selling side. Who wouldn’t want a smoother path to their dream home?

[Check them out](https://orchard.com/) for a free home valuation now — in addition to helping homeowners buy and sell simultaneously, they also have offerings for those looking just to buy or just to sell.

It’s easy to drive lead volume on Facebook, but high-quality leads are in shorter supply. See how Orchard lowered CAC by building high-intent audiences with no-code AI.

How Orchard reaches high-quality home buyers and sellers using predictions

[Saatchi Art](https://www.saatchiart.com/) brings a gallery experience into the art buyer’s home, transforming the way people find and purchase original artwork. But their innovation doesn’t stop there. As more like-minded brands emerge, they knew that being able to quickly activate on customer predictions would give them a competitive edge. To do this, they wanted to target better leads on Facebook for their acquisition campaigns, but to target the best candidates for conversion, they first needed to know more about their existing customers.

## Unlocking unique attributes with enriched data

The first step in giving Saatchi Art a better understanding of their customers was to enrich their first-party data with hundreds of telling attributes from the [Faraday Identity Graph](https://faraday.ai/features/data). Ranging from demographic data to buying habits to lifestyle information, FIG revealed details about the brand’s customers that otherwise may have gone undiscovered.

From there, they generated a customer insights report that broke out the key data that make their customers unique. This included, but was not limited to, home market value, education, and high-ticket home decor spending. These could later be activated to further [personalize customer engagement initiatives](https://faraday.ai/solutions/engagement_and_retention).

## Lead generation on Facebook

For acquisition, Saatchi Art relies heavily on Facebook. However, the shallow insights and increasing costs that come with the platform’s Lookalike audiences made it difficult to optimize their ad spend. Within six weeks of working with Faraday, Saatchi Art had a validated [lead generation model](https://faraday.ai/solutions/lead_management) that seamlessly delivered custom audiences to Facebook. Including valuable leads that Facebook Lookalikes historically excluded, Saatchi Art’s lead generation campaigns performed better and attracted their ideal customers. Spending their Facebook budget on the leads that showed the most promise for conversion lowered Saatchi Art’s cost-per-lead by 51% and cost-per-acquisition by 60%.

Faraday's predictive advertising models helped Saatchi Art score new, unique customers across the country and optimize their Facebook ad spend.

How Saatchi art implemented data-driven predictions to lead generation campaigns

With brand trust at an [all-time low](https://www.havasgroup.com/press_release/havas-meaningful-brands-report-2021-finds-we-are-entering-the-age-of-cynicism/), it’s a good time to ask: is your organization doing the right thing with consumer data? 50% of consumers say they’d pay more for a brand that takes a stand on important issues. With privacy at the heart of a global reassessment of social media, big tech, and surveillance, organizations at the vanguard of this issue will win in 2022.

The good news is that playing fair isn’t all that complicated. “When in doubt, follow your heart,” says Andy Rossmeissl, CEO of Faraday, the leading customer prediction platform. “Our motto from the start has been ‘don’t be creepy,’ and it’s remarkable how far that can take you.”

Looking for specifics? Here are the top 3 rules for using customer data ethically:

## Rule 1: Use identifiers people can recite from memory.

This rule sounds simple, but it’s surprisingly powerful. “Ask your mom if she knows any of her tracking cookies by heart,” suggests Rossmeissl. “Ask yourself what your mobile device ID is.” The digital surveillance panopticon relies on these [long, unique strings](https://www.quora.com/What-does-the-code-for-a-tracking-cookie-look-like) of gibberish assigned to virtually every eyeball in the world.

Instead, ask yourself what identifiers you have that you can actually recite. “I have an address on my mailbox for all the world to see, and you probably do too,” says Rossmeissl. “I put my number in the phone book, and my email address is all over the Internet.”

Relying on real-world identifiers, or “known identities,” has the additional benefit of steering brands away from collecting and using anonymous behavior, such as data collected from unidentified web and mobile visitors. “Until somebody has identified themselves to you," explains Rossmeissl, "tracking their behavior is, frankly, creepy.”

## Rule 2: Use data that comes from commercial behavior

“I call it the ‘laying in bed rule,’” Rossmeissl shares. “When I’m laying in bed and I read a news article on my tablet or like something on Instagram, that’s private. Watching me do that is creepy.”
The surveillance of private behavior has rapidly normalized, much to the dismay of both privacy experts and, increasingly, consumers alike. A 2019 study found that nearly two thirds of Americans believe they can’t go through daily life without their data being collected.

And yet marketers have long known the power of data-driven growth practices. How can brands [use consumer data while still respecting privacy](https://faraday.ai/features/responsible-ai)? Rossmeissl shares:

> We thought long and hard about this when we started Faraday in 2012. We drew on anthropology, architecture, history, and other disciplines for our research, but the result was fairly simple.

> It turns out that commerce is one of the main reasons humans started to live in communities. Markets are some of the earliest forms of non-residential architecture we know of. No matter how you look at it, commerce and the marketplace have been with us longer than virtually any other social structure.

This provides a clue: humans are quite used to buying and selling, and they’re used to doing it in public. We have evolved an innate ability to operate in the marketplace, and an accompanying understanding that this behavior is public.

“What we put in our cart at the grocery store is public,” says Rossmeissl. “What we buy walking around a farmer's market is public. And when we buy online, there's an extension of this understanding. Engaging in commerce is a collaborative act — there's a buyer and a seller — and also a performative one.”

The upshot is that we instinctually treat data arising from commercial transactions as fair game. Luckily, this kind of data is not only the most ethical, but also some of the most powerful available for predicting subsequent consumer behavior. Faraday includes over 300 data points like this on virtually every US adult, but you can also procure your own from reputable licensing groups like Epsilon.

## Rule 3: Let people easily opt out

“Imagine being in a store and being told you can’t leave,” says Rossmeissl. “That goes from creepy to nightmarish very quickly.”

The right to opt out is at the heart of CCPA, the landmark privacy legislation. And while the law only protects California residents, brands should meet its requirements across the board. Luckily, that’s quite simple: provide an easy to use opt-out link, and pass along opt-outs both up- and down-stream to your partners.

Beyond the fact that [honoring opt-outs is actually good for business](https://sendgrid.com/blog/honoring-opt-outs-is-good-business/), it’s the right thing to do.

Is your organization doing doing the right things with consumer data? Here are 3 common-sense rules to follow.

3 common-sense rules for ethical data use 

Launched in 2017, this insurtech company had been using Facebook Lookalikes to build brand awareness and find new customers. Managing everything from will creation to life insurance, this company faces heavy competition with traditional insurance providers, so their acquisition strategy has to be strong.

## Understanding customers for Facebook targeting

Faraday provided the insurtech company with the capability to understand their existing customers and build out the initial Facebook audiences around those insights that would fuel predictive audiences down the road. Optimizing their [acquisition campaign](https://faraday.ai/solutions/customer_acquisition) performance on Facebook would allow them to generate qualified leads efficiently and grow their revenue.

## Customer insights inform lead generation and personalization

Understanding their customers was the first step in knowing who to target in the future, on Facebook or otherwise. Syncing their customer data with Faraday allowed them to gain a holistic understanding of who their customers are in real life. These insights would allow them to know more about the kind of leads they were looking for, as well as inform future personalization efforts. Compared to the rest of the U.S. population, their customers had a few key lifestyle patterns worth paying attention to.

With Faraday's consumer predictions, this insurtech company was able to target leads most likely to convert on Facebook and lower CPL.

How an insurtech company engaged more qualified leads with consumer predictions

The [New York State Energy Research and Development Authority](https://www.nyserda.ny.gov/)(NYSERDA) has worked hard over the years to improve energy efficiency across the state, implementing both residential and commercial initiatives. In 2018, Faraday was chosen by NYSERDA to assist their efforts with a clean heating and cooling community campaign, with the hope that Faraday’s audience targeting capabilities would encourage more New York homeowners to adopt clean energy technology.

NYSERDA wanted to empower New York state’s HVAC installers, distributors, and manufacturers of clean heating and cooling technology with the marketing capabilities needed to deliver direct mail campaigns to households most likely to apply for and install new heat pumps in their homes. Leveraging the Faraday platform would both boost energy efficiency across the state and reduce HVAC businesses’ [customer acquisition](https://faraday.ai/solutions/customer_acquisition) costs.

## Expanding reach with predictive audiences

In the past, HVAC businesses have leveraged traditional segmentation techniques focused on limited data, such as demographics and location of residence. But this method often does not account for variables such as homeownership, property data, or financials. To find new leads that were likely to be eligible for clean energy heat pumps, NYSERDA contractors used the Faraday platform to predict which homeowners in the state would be eligible for and likely to install a new clean energy heat pump. With Faraday’s resulting predictive audience, the contractors reach over 1 million new households with direct mail campaigns promoting energy efficient HVAC systems.

## Audience analysis generated by machine learning models

Comparing audiences generated by Faraday with machine learning models to traditional segmentation methods, households included in Faraday’s audiences were more likely to be approved for a new heat pump and complete an installation. The analysis showed audiences that were 2.39x more likely to be approved for installation and 4.12x more likely to complete an installation.

Using Faraday's predictive targeting models, NYSERDA was able to target over 1 million new households in their direct mail campaign.

How NYSDERA drove energy efficiency iniatives using predictive audiences

With the rise of e-commerce, the lingerie market is seeing more competition than ever. One of Faraday’s clients, an established luxury lingerie brand, knew they needed modern marketing solutions to stay relevant. Over the past decades, the brand has amassed a loyal following that spans the globe, thanks to their focus on providing beautifully hand-crafted garments. But to keep growing, their attention to customers can’t stop at the end of the production line.

## Customer profiling

Focusing on improving their holiday campaigns, the brand leveraged [predictive audiences](https://faraday.ai/features/predictions) to reach high-LTV leads and developed insightful personas to further personalization initiatives. Leveraging rich consumer data and predictive models, Faraday has helped the brand get in front of more high-LTV customers and better engage their existing ones with personalized experiences.

## Personalized messaging

After surfacing deep customer insights with the [Faraday Identity Graph](https://faraday.ai/features/data), Faraday generated data-driven personas. Unlike traditional customer personas, Faraday’s are generated with an algorithm using enriched customer data. They are also unique in that they can be stored in any marketing system to inform future engagement and make executing persona-based campaigns a breeze.

Faraday’s predictive personas allow brands to improve personalization initiatives and can help brands stay relevant to their customers. With the Faraday platform, the lingerie brand [pushed their personas seamlessly into Iterable](/integrations/predictions-with-iterable), their email marketing platform. Storing them there makes it easy to segment audiences for future engagement campaigns to include curated creative and messaging.

## Seeding audiences on Facebook

To capitalize on increased traffic around the holiday season, the brand used their newly built personas to seed high-LTV audiences on Facebook, making sure to include only those leads who were the likeliest to convert and stick around for the long-run.

Spending their Facebook budget on the personas that showed the most promise or high-lifetime value resulted in 19% higher click-through-rates, 5% higher average order value, and 43% higher conversion rates.

Discover how this luxury lingerie brand ran a highly personalized, hyper-targeted holiday campaign driven by consumer predictions.

How a luxury lingerie brand drove personalization and high-LTV audience seeding with predictions

Founded in 2016, organic skincare brand [Ogee](https://ogee.com/) relies heavily on social media for brand awareness and acquisition. Between 2018 and 2019, the brand was using Facebook Lookalikes and, as a result, saw a surge of new customers. However, Facebook didn’t give them the crucial insights needed for improved audience targeting and personalization.

As the customer base grew, Ogee wanted to focus on high-LTV customers to maximize their ROAS. So, they teamed up with Faraday to learn more about their customers, predict customer lifetime value, and target high-LTV audiences on Facebook.

## Enhancing first-party data to understand customers outside of purchases

Ogee’s customer base quickly evolved as the brand grew. To understand more about their new customers, Faraday dug deeper into the [data](https://faraday.ai/features/data), enhancing Ogee’s first-party data with rich third-party attributes to give the brand a more holistic picture of who their customers are, outside of their past transactions. Key findings included that many customers were college graduates, upper middle class, and had a history in buying beauty products.

## Using LTV predictions to identify best customers

To understand which types of customers were still worth going after, Faraday [predicted](https://faraday.ai/features/predictions) the customer lifetime value (LTV) for three distinct groups of customers, segmented by their date of first-purchase. Faraday predicted how much each group would spend over the following 6 months and over the following 12 months, using a probabilistic model that took into account each group’s transactional history. Calculating LTV can be a challenge for many brands, but it’s a crucial metric that influences revenue forecasting, ad spend, and fundraising efforts. Traditionally, the margin of error for these calculations is pretty high, but Faraday came in with an impressive 7% MOE when predicting Ogee’s customer LTV.

## Propensity models targeting high-LTV customers

To continue to attract the kind of high-LTV customers growing their brand, Ogee worked with Faraday to leverage propensity models, scoring the entirety of the U.S. to see who would most likely become a high-LTV customer. The top 1% of the scored group comprised the [custom Facebook audience](https://faraday.ai/predict/pipelines/likely_buyers_in_facebook) pushed from the Faraday platform. Ultimately, the predictive audience outperformed Ogee’s traditional Facebook Lookalike audiences. Spending their Facebook budget on predicted high-LTV leads lowered Ogee’s cost-per-result and significantly lifted the brands ROAS on Facebook.

Faraday's custom lookalike audiences and customer lifetime value predictions allowed Ogee to see massive results in their Facebook campaigns.

How Ogee used LTV predictions and predictive acquisition audiences during growth

The pandemic has destabilized many consumers’ financial situations, forcing them to reprioritize their finances in order to stay out of debt. Because of this, businesses offering creative solutions that allow individuals to pay back debt, invest, or easily start a savings account have become increasingly popular.

One of these businesses is [Happy Money](https://happymoney.com/), a fintech company on a mission to turn borrowers into savers, specializing in helping people pay off their credit card debt and save up for the future. Featured by publications like [Forbes](https://www.forbes.com/sites/donnafuscaldo/2019/09/05/happy-money-raises-70-million-at-a-valuation-of-nearly-500-million/?sh=6b37d1bd5777), The Wall Street Journal, and Fast Company, Happy Money has over 100K members and has helped pay off over \$2 billion in credit card debt by partnering with financial institutions willing to lend money.

Happy Money started working with Faraday to improve their marketing campaign performance by connecting to the people across the country who are in need of their financial services.

## Predicting optimal locations for expansion

In order to reach new leads across their marketing channels, Faraday built [predictive models](https://faraday.ai/features/predictions) using rich consumer data to find potential Happy Money members, identifying candidates interested in paying down credit card debt. This gave Happy Money access to high-performing audiences that they were able to push directly to Facebook during Q1 and Q2 2020.

This is particularly exciting because, despite the economic downturn in the beginning of the pandemic that accompanied high rates of job loss and hardships for many businesses, Happy Money was able to reach the consumers who would benefit personally from the brand’s services.

## Taking a multichannel approach

Facebook isn’t the only platform where Happy Money advertises. Like any smart brand, they know that reaching new leads on one social media platform just doesn’t cut it — they need to utilize their audiences across multiple acquisition channels.

Faraday’s custom audiences are unique in a number of ways. First off, they allow brands to get in front of consumers that they may otherwise not reach via traditional segmentation or Facebook’s own lookalikes. Second, the audiences are portable, meaning they can be optimized for and deployed to any marketing channel — like Facebook, Snapchat, direct mail, and ad display networks like Verizon Gemini — to support a strong omnichannel strategy.

These custom audiences aren’t just one-off lead lists, which is how a number of lead generation tools work. The Faraday platform delivers new, updated audiences every month to Happy Money’s acquisition channels to ensure that Happy Money is always reaching the most qualified leads.

## Using customer personas to seed new audiences

Within every brand’s customer base, there are multiple types of customers, which can be analyzed and grouped by persona. To hone in on ideal members, Happy Money is working with Faraday to generate audiences based on existing member personas.

[Faraday’s personas](https://faraday.ai/predict/category/persona_assignments) are developed with machine learning models to mitigate human bias and eliminate the chance of overlooking a significant customer type. Seeding audiences with these personas has many advantages, arguably the most important of which is the ability to personalize ad content and campaign messaging to maintain relevance with each audience.

As Happy Money continues to strengthen their omnichannel approach, these multichannel audiences will hopefully prove to be useful in reaching more people who look like the members that have grown Happy Money’s business the most.

How the booming FinTech company reaches the right consumers with Faraday's predictive targeting solutions.

How Happy Money optimizes omnichannel marketing with data-driven audiences

During the pandemic, interest rates for home mortgages reached all-time low. As people were spending significantly more time at home, buying a house — especially for those who relocated out of denser cities — has become a more practical option than renting. In August 2020, [home sales shot up](https://www.businessinsider.com/how-2020-broke-the-housing-market-inventory-could-run-out-2020-9) to reach a 14-year high.

Millennials in particular have made their mark on the real estate business, as they now make up the largest share of home buyers in the country, according to the [National Association of Realtors](https://www.nar.realtor/research-and-statistics/research-reports/home-buyer-and-seller-generational-trends). However, many businesses that service the home, like HVAC contractors, report that they [do not focus on millennials](https://www.achrnews.com/articles/144348-ignore-millennials-if-you-dont-want-to-reach-homeowners) for their marketing campaigns. This is their loss, especially since millennial homeowners are at their fingertips on social media and digital platforms, where targeting younger demographics is a breeze.

So, if you’re in the business of home renovation, DIY tools, residential energy efficiency, or HVAC, consider the following when marketing to millennials — a generation eager to take you up on your services.

## Find millennial homeowners on the right channels

Millennials are a digitally native generation. A [global survey](https://www.gwi.com/reports/millennials) conducted by the Global Web Index in Q3 2020 looked at more than 66,000 internet users and found that millennials ages 24–37 spent an average of 2 hours and 30 minutes each day on social media alone.

If your brand is not capitalizing on social media, digital ads, and OTT options like streaming channels to reach millennial homeowners, you’re missing out on crucial brand awareness and conversion opportunities.

In addition to actively targeting specific audiences, be sure your SEM strategy is up to par, as millennials are big online researchers. Back in the day, newspaper and yellow pages ads may have cut it, but that’s all switched over to online search engines now. Ensure that your areas of interest and/or operation are prioritized in any search your brand may be relevant to.

And once you’ve got your lead on the hook, you can ease their journey to conversion by communicating on the platforms that are most convenient for them; this may be SMS text, video chat, or a website chatbox. From getting a quote for a solar installation to matching a desired paint color, millennials value seamless communication that meets them where they already are in the digital realm.\

## Cash in on millennials' renovation obsession

To accommodate growing families, remote work, and even houseplant obsessions, millennials are big into remodeling and DIY renovations — they’ve even been coined the “renovation generation.” Compared to both older and younger groups, millennials are [3X more likely](https://www.homeadvisor.com/r/wp-content/uploads/2020/12/DP6355-StateOfHomeSpending-2020-R4.pdf?ref=faraday-blog) to take on home office projects and additions. It’s imperative that contractors and home service providers take these trends into account when fleshing out marketing campaigns.

This could mean kitchen remodelers including messaging around spending more time cooking in the kitchen since dine-in options are still limited around the country; or perhaps construction companies advertising the ease of adding on a home office to accommodate remote work. Even video-based consultations can be a deciding factor for homeowners concerned about social distancing or eager for ease of access to an expert.

No matter the product or service, using digital marketing campaigns to introduce ideas for how millennials can improve their at-home lifestyles may spark interests homeowners didn’t know they had, bringing them closer to converting.

## Emphasize eco-friendly products and services

The millennial homeowner is no stranger to “going green” — this messaging has been prevalent throughout much of their life, so much so that [73% of millenials](https://www.inc.com/melanie-curtin/73-percent-of-millennials-are-willing-to-spend-more-money-on-this-1-type-of-product.html) are willing to pay more for sustainable products. Green features are especially popular when they’re sure to lower utility bills in the future.

[During the pandemic](https://porch.com/advice/home-improvement-trends-covid), 34% of homeowners have made their homes more environmentally friendly, with half of that percentage being millennials and Gen Z. On average, millennials are going to spend $10,000 this year alone on home improvement projects, and they recognize that their return is greater if those projects include eco-friendly materials and products.

So whether you’re offering the installation of more environmentally friendly heat pumps, solar panels, or even sustainably harvested hardwood flooring or low VOC paints, make a point to emphasize that your products are eco-friendly to further appeal to millennials. This angle may be even more effective if used to support social media campaigns, as those platforms serve as a hub for eco-conscious consumers proliferating sustainable home improvement solutions.

## Tap into trends to market to millennials

As a digitally native generation, millennials easily take to social media trends, especially those that are good for their wallets, the environment, and lifestyles at home. Tapping into the right channels with messaging relevant to millennial interests can improve the performance of your campaigns and attract the consumers who hold the most spending power in the economy.

Digital campaigns, relevant messaging, and eco-friendly products are key to wooing the largest share of homebuyers in the country.

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