[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.

Marketing to millenials: Tips for home services companies

Work-life balance has been put to an extreme test this past year, with many people working from the same place they spend their free time. And for those with family obligations around schooling — as well as entertaining kids who aren’t doing their usual extracurricular activities — the notion of “free time” may hardly exist. In the sweet moments of respite, self-care is queen.

Over the last few years, self-care has evolved to be more than a fleeting trend in the health and wellness industry — it’s an entire market that spans fitness, nutrition, personal care, and beauty products. From books to vitamin supplements, it encompasses a variety of products, setting up a wide range of brands for entry into the market.

As more options pop up for customers, engaging leads and building brand loyalty may prove to be difficult. Luckily, there are steps marketers can take to capitalize on the growing self-care industry and reap the benefits of its popularity among consumers.

## Account for customers’ shifting finances

There’s nothing worse than being targeted by a brand for a product that you can’t afford. Since many consumers’ finances have taken a beating during the pandemic, it’s imperative to recognize that the people you included in target audiences a year ago may not be able to afford your products now.

To mitigate this issue, many self-care brands have begun partnering with fintech lenders to offer post-purchase payment plans. Not only does this make products with a higher price point available to a larger swath of consumers, but it also indicates to your customers that your brand recognizes upfront payments can be a challenge for some individuals. This type of signal can be especially important if your product is considered a luxury or nonessential item.

Another way to mitigate consumers’ change in financial standing is to segment audiences by financial bracket or income, pushing ads and promotions to each segment featuring products that are actually feasible purchases. This could improve your ad campaign performance, increasing conversion rates and repeat purchases.

## Get to know new types of customers

As brand loyalty shifts and the online presence of self-care products and services grows, many brands have seen an influx of new customers that don’t necessarily fit the mold of their existing audiences. Engaging these new customers may be different from what you’re used to.

One way to understand shifts in your audiences is to leverage your historical customer data to generate [personas](https://faraday.ai/features/predictions). With insight into your various types of customers, old and new, you can craft messaging that takes into account their respective needs and lifestyles. This may manifest as certain product recommendations in email campaigns, or perhaps direct mailers that feature promotions specific to each persona’s interests.

Additionally, several brands are using data science to predict customer lifetime value, which helps them be more strategic about discounting, CAC thresholds, etc. You may be surprised which customers are likely to take their business elsewhere, and which are going to be loyal for the long run. Not only does this analysis help brands predict future revenue more accurately, but it also allows marketers to focus on engaging the customers who will contribute most to that revenue.

## Determine which customer engagement strategies work for your brand

This article is by no means an exhaustive list of what marketers advertising self-care products and services can do to improve their customer engagement. And not everything touched on here fits every brand’s marketing strategy. By testing new channels, messaging, and audience segmentation, you can figure out what works best for your brand and your customers.

Whatever you end up doing, be sure to include data in the process; from building audiences to generating personas, data-driven marketing is what will set you apart and grow your self-care brand most efficiently.

As the self-care industry becomes increasingly competitive, brands must leverage data intelligently to keep customers engaged.

Customer engagement strategies for self-care brands

Audience overlap is a common issue marketers face when advertising on platforms that build native audiences or lookalikes. Often marketing teams will create two separate ad sets for a campaign, but end up reaching more or less the same audience despite trying to target different audiences. So rather than expanding their reach, brands are inadvertently oversaturating their audiences — which can frustrate consumers and result in wasted spend.

## What causes audience overlap with Facebook Ads?

Honestly, we aren’t sure. Many advertising platforms that generate audiences using brands’ uploaded first-party customer data in combination with the platform’s third-party data — Facebook, for example — don’t provide much insight into how they build those audiences. Faraday Data Scientists have seen time and time again Facebook pulling the same people into audiences, regardless of the target result (e.g. add-to-carts, clicks). We chalk it up to the training data.

## How audience overlap impacts brand reach

Audience overlap costs marketers valuable opportunities to reach potential customers. To serve the best ad to as many of the best leads as possible, brands must know who their customers are — but tracking just consumers’ digital footprints to guide ad creative isn't enough. One way to mitigate this issue is to upload custom audiences built with real-world, offline data.

We've seen a significant reduction in overlap between Faraday's custom audiences (from our third-party consumer database) and Facebook Lookalike audiences.

This approach has two key benefits: it addresses the problem of oversaturation and expands advertisers' potential reach beyond the ad platform's built-in capabilities.

## Tools to monitor and reduce audience overlap on Facebook and other channels

When ad sets overlap, they can compete against each other for visibility and unnecessarily increase marketing costs. You can (and should) monitor [overlapping audiences in Facebook](https://www.facebook.com/business/help/1679591828938781?id=176276233019487) monitoring overlap in the Facebook Audience Overlap Tool and uploading custom audiences that limit any duplication will be key here when thinking about ways to optimize spend and lower customer acquisition cost.

Overlap can happen on any channel where you build lookalike audiences, whether it’s Facebook or Hulu or Snapchat. Some platforms have taken measures to decrease the risk of oversaturating audiences by installing [frequency caps](https://www.advertisingweek360.com/hulu-a-better-experience-for-viewers-a-better-home-for-advertisers/?ref=faraday-blog) on ads. Hulu, for example, now makes sure that no ad is shown more than twice in an hour. But some customers have still reported seeing the same ads many times. This may be because of audience overlap — when Hulu runs an ad against multiple audiences, customers that are in more than one audience could see it again and again.

So, just because platforms are working to make ad experiences better doesn’t mean that brands don’t also have to put in the work. Because ultimately, this sort of viewer exhaustion can drive customers away, rather than reinforcing brand recognition and leading to conversions.

Learn how custom third-party audiences help reduce audience overlap across Facebook Ads campaigns.

All posts