AI, startup hacks, and engineering miracles from your friends at Faraday

Building a sexual health and wellness brand for the modern consumer: an interview with Eva Goicochea, founder and CEO of maude

Alexis Hughes on

Faraday Spectrum interview series with maude
We had the pleasure of speaking with Eva Goicochea, founder and CEO of maude, a Brooklyn-based sexual health and wellness startup, founded on the values of simplicity and inclusivity. Launched in April 2018, maude is redefining the conversation and culture around sexual wellness with a line of sleek and simple sex essentials and a customer-centric approach.

maude: from inception to realization

Eva Goicochea's journey from being Head of Social Media, Culture and Hiring at Everlane to founding sexual health and wellness startup, maude.

After studying marketing, I had a stint as a legislative aide in healthcare by happenstance and it became formative. Later on, I went back into marketing, eventually landing at Everlane four months after they launched. When I left in 2013, I wanted to find a startup in healthcare / wellness that I was just as excited by as I was Everlane and I couldn't find one. While working with clients building their brands, I also started a watch company, Tinker, with two other founders and my husband (great experience for building product). Randomly, we were all kicking around this idea of maude, wondering why there was no better brand in the space and if it was something we should venture out and build. The lightbulb went off — this was the idea I had been waiting for. The rest of the team wasn't actually interested in launching maude, but I was full-in.

In 2015, I started working on the idea, moved to NYC in 2016, raised money in 2017, and went to market in 2018.

Brand loyalty vs. Brand affinity

With big brands like Trojan and K-Y dominating the sexual wellness market, introducing maude required a thoughtful approach and an understanding of consumer needs — which actually helped to set the small company apart from the long-standing giants.

We launched with condoms, two lubricants, and a vibe with the idea that we could solve for the chasm that exists in the industry. Sexual wellness has always felt like it's in two corners: clinical and maybe on the aisle where Trojan dominates — they own 70% of the market and they're very condom-focused. And then you have sex toys and these dark corners of seedy shops where you buy them, even though a vibrator, for instance, is actually a really necessary tool for many, many people. Universally, I was hearing from people — no surprise — that in both places, buying these products is incredibly uncomfortable.

And so I thought, “Why is there no DTC brand for all people where you can buy all of these essentials? These products need to be together. Plus, if we launch with one over the other we're going to get pigeonholed.” And so that's what we did. The past year has proven, also, that people were ready for a new condom brand in an industry with giants.

The thesis here was that because there's a monopolization, there's brand loyalty — people buy Trojan — but there's no brand affinity. And it made no sense to me, or when I spoke to other people, that the sexual wellness industry is so far from what a consumer wants.

Since starting the company, I've done so much more research about the history of this space, specifically condoms, and these companies that have dominated for over a hundred years. Moreover, the industry has been so tied to socio-political movements that somewhere the basics — the human side of sex — has been lost. For too long, it's been something tied to shame or family planning rather than “Sex is human, and all people need condoms for protection. They're the only form of protection against STIs and pregnancy, period.” It's super simple.
maude Staycation retail popup shelf
Photo: Nicole Franzen for maude

Building a human-forward company

Goicochea founded maude on a mission that deeply values their customers, giving them more reasons to invest in the brand and products.

There are two ways companies are led: one is by product, and one is by mission. And a lot of [direct-to-consumer] companies lead by product, essentially saying that their product will change your life. Sometimes that's true; sometimes they are great and innovative. But I think the reality is that the longevity of brands lies in its values and in its true mission.

We want you to understand maude, not because you know every product, but because you align with the brand for its values. The opportunity for any company, I believe, is in creating a community that cares about the mission. For us, it's being a human-forward company and changing the conversation and understanding around the idea of sex.

I used this as an example the other day, whether we love it or hate it: Starbucks created a new language for coffee. Pretty much in every corner of the world, you can find a Starbucks and people know what a latte is. That changed the language of coffee for most people. And that's what we want to do. (Which is going to take a long time.) So given that mission, let's look at the long view.

A strategy of subtlety: Making sexual health and wellness approachable and accessible

Many emerging sexual health & wellness and sextech brands make pleasure a centerpiece of their marketing strategies, which can be exciting for more progressive consumer demographics, but alienates others. In light of this, maude has taken a gentle approach to addressing sex and pleasure in its marketing campaigns and in the conversations it facilitates at events.

I often compare what we're doing to food. For instance, say you're sitting at the table with someone who drinks Folgers (no dig on Folgers) and you're trying to talk to them about third wave coffee. Talking about coffee from the angle of what you should do, or “This is better” or “We know best,” is not going to disarm them. What's going to disarm them is giving them a cup of coffee that's better and then creating common ground (no pun) from which you can then talk coffee. In short, shoveling ideas in someone's face is not going to make them more open.

That's why we don't take an aggressive approach. We want people to learn about maude, try the product, and make the decision for themselves. To date, we have a strong word of mouth and that organic change can't be forced.

Speaking of talking at people, I typically don't even use the word “pleasure” because I think the idea of pleasure is subjective. We create well-made products for your intimate life, and how and with whom you use them is up to you — we can't tell you what your pleasure is. I think there's a lot of appropriation of this idea of pleasure happening right now, and that in and of itself is actually quite exclusive, as is making the idea of sex political.

I'll say it a million times: Sex is human. One of the words I do love actually, is “leisure.” Leisure — or in this case helping you make time for intimacy — is what maude is here to do.
maude Staycation retail popup bed
Photo: Nicole Franzen for maude

Carving out space for sexual wellness in advertising

Categorized as “Adult Products and Services” on Facebook, what's deemed as appropriate for sexual wellness brands' ad creative is limited. While some brands have aggressively pushed back against Facebook's restrictions for this product category, maude believes in creating a new vision for advertising these products on Facebook altogether: one that works to celebrate and share the inclusive values the brand is built on.

We're not actively antagonistic against Facebook — of course we get shut down, and it's really frustrating that it's a blanket rule for “Adult Products and Services.” But we're not angry about it. The reality is that it sex is still taboo and it is still clinical, and it is up to us as a company to carve out a new third lane that creates the societal acceptance needed to eventually change policy. So, while there are other approaches, we're going focused and continuing to come at this from a common sense, matter-of-fact, friendly, happy way, with a long view. It's going to take time.

Staycation: an exploration of temporary retail

Staycation is maude's Summer 2019 pop-up shop in Brooklyn. A collaboration with a multitude of DTC brands, the space shows how the brands' products live well together and can integrate into a consumer's life.
maude Staycation retail popup sign and Floyd couch
Photo: Nicole Franzen for maude

Right now, as we're sitting in this space (our retail front across from our office), it feels more like an installation, and I think it works in that context better. You walk in and you get the idea of this “modern apartment” and where maude lives in your life. And that was actually the whole point — to give the right context. Before, when it was the winter studio and it was just our brand, people were still afraid to walk in, no matter how minimal and friendly the space was. Staycation has provided a greater vision for how we can live as a brand out in the world and allowed for us to actually pitch forward-thinking retail partners who are carving out a space for sexual wellness.

If somebody offered you $100 million for your company, would you take it?

No. The purpose and opportunity for maude is to change the language and culture of sex, and that is going to take time. If put in the wrong hands with speed, it's not going to happen and we'll never reach our real potential, which would ultimately be a disservice to our customers. In short, I'm in it to change history and I believe we will.

This interview has been edited for clarity and flow.

Spectrum is Faraday's exclusive interview series, highlighting DTC brands revolutionizing their industries with innovative products and growth marketing strategies.

Third-party data in marketing: Why it's important and how to protect consumers' privacy

Alexis Hughes on

third-party data iceberg illustration
The use of third-party data isn't new, but it's becoming a necessity as businesses shift to a customer-centric approach. Marketers everywhere are realizing that first-party data is only the tip of the iceberg when it comes to understanding their customers.

Pitney Bowes and Forrester report that 92% of marketing and data analytics professionals agree that the rise in digital technologies and interactions has increased the need for bringing outside data into their companies. While it may be as simple as understanding your existing customers' household and financial standing, with third-party data you can also gain deep insights into your leads on a known-identity basis.

Overall, leveraging third-party and first-party data adds breadth and depth to your customer insights, informing better branding and messaging decisions, personalization efforts across channels, and taking much of the guesswork out of targeted and location-based marketing campaigns.

Customer identity resolution

customer identity resolution illustration
The capability to bring together first-party data from various sources and third-party data to compile a unified picture of each customer is increasingly valuable. In 2018, spending dedicated to identity data assets grew by more than 50%, to a total of $846MM.

Personally identifiable information (PII) is crucial to connecting the dots across multiple touchpoints (online and offline) to form a holistic picture of your customers and prospects so you can reach them with content that will resonate with them through the channels that matter.

Using third-party data to improve personalization

marketing personalization illustration
In a time when almost all consumers prefer ads and products that are relevant to them, knowing how and when to serve your target market is crucial to effectively engaging your customers. According to Forbes, right now, 46% of marketing executives are not where they want to be in terms of delivering personalization, and 57% say that they hope to advance their personalization initiatives over the next year.

Enriching your first-party data with third-party information on your customers' financial, household, transactional, or lifestyle categories gives you a clearer idea of what your customers look like in real life.

To take it a step further, enriched customer data helps machine learning algorithms build better models. Cluster models, for example, sort individuals into distinct groups based on common attributes. These groups, or personas, can affirm your intuitions about what your customer base looks like, but may also surprise you by revealing significant groups you hadn't known about or previously considered important.

How third-party data helps optimize ad targeting and nurture campaigns

predictive scoring targeted marketing illustration
If you're using predictive lead scoring capabilities, the accuracy and precision of those scores improve with the quality and quantity of third-party data that you introduce. This not only benefits your leads' experiences, as they'll receive content that better aligns with their interests and where they are in their customer journeys, but it will save you time and money when you're deciding how to prioritize your outreach.

A popular way of leveraging third-party data with predictive modeling for digital marketing is Facebook lookalike audiences. But since the platform shut down advertisers' access to this data in April of 2018, gaining deep insights from Facebook has been a struggle for many businesses that are trying to better understand their audiences and target the right consumers.

If you enrich your first-party data with third-party attributes, you can gain insights on a granular level that you aren't getting with Facebook and other marketing channels. You can then segment known-identity audiences based on certain attributes — or develop in-depth personas for segmentation — and push the appropriate ad creative to those individual segments with the goal of increased, personalized engagement.

This goes for not only new leads you're nurturing, but also for the customers you're actively engaging. Pitney Bowes and Forrester's survey showed that 83% of respondents realize timelier and contextually relevant customer experiences are a high priority when it comes to optimizing their marketing strategies. With nurture campaigns, timeliness and relevance are key components for success.

Another advantage of leveraging third-party data is the ability to match site's captured emails to real people. This allows you to bucket leads into certain personas for more personalized nurture campaigns that will pull them through their customer journeys with you. Your leads are more likely to receive messaging that aligns with where they are in their individual journeys, and it will save your team time and money when you decide how to prioritize your lead outreach.

customer lifecycle optimization whitepaper

Enhancing geospatial analyses with third-party data

geospatial analysis illustration
Geographic data has obvious benefits, but incorporating additional third-party in geographic analyses improves the quality of the insights. Knowing where your ideal customers live is one piece of the geomarketing puzzle, but gaining an understanding of how your audiences will best interact with your ads offline is achieved by knowing more than just their geographic location.

Attributes like household information, transportation preferences, and lifestyle data helps you prioritize where you place ads, as well as where you might establish new brick-and-mortar presences. A subway ad or billboard placed in your customers' neighborhoods can be a great way to advertise your e-commerce business for those who don't live near a storefront, but for customers who are in your brick-and-mortar trade zones, perhaps a direct mailer advertising an in-store sale would better drive business.

From a creative perspective, audiences can vary widely depending on their physical locations, so the messaging and images chosen for your campaigns should be curated for specific audiences in particular geographies. Providing relevant content increases your chances of audience engagement, so capitalizing on the insights provided by third-party data is a necessity.

This is the case with SEM advertising, which segments audiences by geographic location. With the insights gained from third-party data, you can optimize your SEM spend by targeting areas where higher-value customers reside, spending less on areas that aren't as likely to bring in revenue.

Using third-party data ethically

data privacy security illustration
With the rise of regulations like GDPR, privacy and validity of data are prominent concerns when using third-party data and PII. However, there are ways to ensure that your customers' and prospects' privacy is protected. You want to be sure your data comes from a verified source, isn't dangerously invasive, and is leveraged to benefit the customers you're targeting.

Social scraping is a common tactic, and it can provide large categories of data on behavioral tendencies, consumer habits, and some personal information, though this data may not always be entirely accurate. At Faraday we avoid social scraping in favor of canonical sources of information from established third-party data vendors. Vendors like Epsilon verify the accuracy of the high-quality data we license and leverage for our partners.

Faraday's Director of Data Science, William Morris, notes that we sidestep many consumer privacy issues by dealing with datasets that categorize data, such as consumer purchases, by type of product and frequency, rather than the exact stores where those purchases are made. This leads to a significant lift in machine learning models' predictive capabilities without being invasive from a privacy standpoint. Additionally, each of our clients' customer data is siloed using industry-standard practices to protect the privacy of each clients' customers.

Faraday also actively works to build models that are agnostic to a person's membership to protected classes. We exclude potentially harmful categories like ethnicity, religion, or primary language data, as these can disenfranchise certain groups of the consumer population. As an additional security measure, we employ a suite of tools for post-model checking to ensure that attributes that could indicate a person's race or class don't make the models biased or adversely impact a population.

Taking into consideration these types of ethical practices is important when exploring your own use of third-party data.

blog_cta_faradiy

How customer-centric marketers use machine learning

Alexis Hughes on

You've probably noticed the growing hype around artificial intelligence (AI) in marketing. From chatbots to content creation to programmatic advertising — it seems like every other MarTech or AdTech platform is baking in some sort of AI capability.

With so many applications, it's easy to lose sight of what's most important in implementing an effective, optimized marketing strategy: deeply understanding your customers.

machine_learning_customer_insights_graphic

According to Forbes Insights, only 13% of businesses express a high degree of confidence that they are making the most of their customer data.

Stepping back, what does AI even mean for marketing?

At a high level, AI refers to a computer's replication of some aspect of human intelligence — pretty ambiguous, right? AI, as it exists today, is an umbrella term for a range of computer-enabled data analysis techniques — the most relevant and widely-practiced in marketing being machine learning.

Machine learning (ML) is the process of training computers to “learn” to recognize important patterns and trends in large datasets, with the goal of developing data models that can quickly categorize new data inputs and predict likely outcomes.

So, what does that mean for you, the customer-centric marketer? When using your customer data, or training data, as the basis of machine learning models, you can start to generate deeper customer insights and make better behavioral predictions. These can be around your prospects' and customers' likelihood to convert on certain campaigns, increase their purchase frequency, churn or lapse, or something much more specific.

Leveraging machine learning in your marketing strategy is no longer a luxury — it's a necessity. As competition increases and ad space gets more crowded, consumers have more choices of businesses to engage with, making machine learning critical to efficiently reaching the right people and keeping your customers engaged.

ML-driven insights marketers can't ignore

It should come as no surprise that the world's top brands are efficiently scaling growth by leveraging machine learning to prioritize their resources and personalize experiences across their customer lifecycles.

Here are some of the most important ML-driven insights marketers are using to craft better customer experiences and optimize their performance.

Behavioral insights and predictions

A vital piece of giving your prospects and customers a memorable experience with your brand is knowing who to engage with and when.

Have you ever been in the position as a consumer where you're targeted with ads that don't align with who you are or where you are in your customer journey? Perhaps you see an ad trying to get you to buy an item you've already bought, or offering you a first-purchase discount code when you're already a customer.

As a consumer, these experiences can be annoying and frustrating. And as a marketer, your message can end up diluted instead of impactful.

Behavioral predictions are crucial to proactively engaging your customers. Rather than reacting to your customers' behaviors, you're able to anticipate them and market to your most valuable customers at the right time, with content that corresponds to where they are in their journeys. This helps you prioritize your resources, optimize your marketing spend, and cut through the noise to better reach your target audience.

How can machine learning help predict customer behavior?

machine_learning_decision_tree_icon

Relatively straightforward machine learning algorithms can uncover predictive patterns hidden deep in your customer data. The random forest, or random decision forest model, analyzes your historical customer data, building a series of decisions trees to predict the likelihood that future inputs (e.g. new leads) will result in a target outcome (e.g. make a purchase).

If you advertise on Facebook, you've likely come across lookalike audiences, which are generated in a similar way. Using lead conversion as the example outcome, these models essentially predict the degree to which a new lead best “looks like” leads who've successfully converted to customers in the past.

Naturally, the data used to train or build your behavioral models will influence how they make predictions. Done properly, these predictive insights can have a tremendous impact on your return on ad spend, overall customer acquisition costs, and customer satisfaction.

saatchi_art_lead_gen_case_study

Persona-based insights and predictions

While predicting your customer's next move is immensely helpful in reaching the right people at the right time, it's not where the road to truly optimized marketing ends. Effective and thoughtful engagement requires an understanding of who your customers are as real people, so you can create hyper-personalized experiences that evoke emotional responses.

Salesforce Research revealed that 84% of customers say that being treated like a person is very important to winning their business. If you show your audience that you understand what motivates them to interact with you, whether they're an early prospect or a loyal customer, the relationship and trust between you and your customers grow stronger.

So how can machine learning help you personalize experiences at scale?

Customer clustering

Buyer personas, semi-fictional representations of your target customers, are instrumental in creating personalized content and creative that truly resonates with them. Traditionally, personas were created using basic demographic data, some psychographic data from surveys or focus groups, and a good amount of human intuition. While this approach has worked for years, it leaves too much room for human bias.

Customer clustering leverages a different machine learning technique than behavioral modeling: unsupervised machine learning. Rather than uncovering patterns that are predictive of a known outcome (e.g. likely to convert), unsupervised algorithms, like K-means, sort data into distinct groups based on shared attributes. The resulting groups, or clusters, form the foundation of unbiased, truly data-driven personas.

machine_learning_cluster_icon

As time goes on and new data is collected, running the clustering algorithm again may reveal new emergent personas, enabling you to refresh your messaging, creative, and other personalization efforts to stay relevant as your customer base evolves.

Burrow, a disruptive direct-to-consumer furniture brand, uses ML-driven personas to identify what color couches their audience segments see in targeted ads. They found that customers who are older, live in single-family homes, and have kids are more likely to buy couches in darker colors; customers who are younger, live in apartments, and have few or no kids are more likely to buy couches in lighter colors. With these insights, Burrow was able to push creative that reflected these attributes to the audiences that possessed them.

burrow_omnichannel_case_study

Location-based insights and predictions

Virtually all consumer-facing companies need to consider location in their marketing strategies, whether it's out-of-home advertising, brick-and-mortar marketing, or geotargeted search campaigns. However, these tactics are often expensive and difficult to do well.

geospatial_intelligence_icon

Geospatial intelligence refers to a suite of geospatial analysis techniques enhanced with a combination of behavioral and persona-based insights. Whether you're considering increasing investment in your existing markets, expanding to new ones, or looking to drive foot traffic to specific retail or branch locations, incorporating predictive insights into your geospatial analyses can drastically improve ROI.

  • Predictive penetration analysis aims to identify the maximum return you can expect from further investments in your existing markets. The resulting insights can help you understand the performance of your existing sites and determine whether you should increase investments or cut back entirely.
  • Predictive market analysis identifies specific hotspots of existing customers and customer lookalikes to guide where you should put new sites and optimize acquisition-focused out-of-home and geo-targeted SEM campaigns.
  • Predictive trade area analysis identifies the maximum distance customers are likely to travel to your existing retail sites. The resulting insights can help you optimize individually-targeted and geo-targeted campaigns focused on driving foot traffic to those sites.

Implementing machine learning

While several complex applications of AI are still years — or even decades — away from being fully developed, the democratization of machine learning is enabling nimble marketing teams to generate these predictive customer insights without having to spend millions on expensive consultants or hire large data science teams.

If you're considering adopting machine learning or looking for ways to expand your analytics team's bandwidth, our article, Is your marketing team AI-ready?, discusses important considerations to ensure successful implementation.

how_to_build_ai_marketing_stack_guide


The DTC movement, AI, and snowshoes

Macallan Atkins on

Last week the Faraday sales team took some time off from the usual day-to-day grind to reflect on the last year, talk about emerging trends in the consumer landscape, and get some much-needed exercise in the Green Mountains of Vermont—I'll admit they're a little greener in the summer.

faraday-sales-retreat-2019

We briefly talked goals and tactics (would it really be a sales retreat without some numbers?), but the bigger discussions revolved around Faraday's why — specifically, why data-driven companies will eventually dominate every consumer market. I'm not going to pitch you here, but I will share my biggest takeaways from the day...

  1. We've all noticed the direct-to-consumer (DTC) movement that's rendering traditional marketing channels obsolete. Bypassing distribution channels is better for the bottom line and gives brand-manufacturers greater control over end-customer data—that is to say, meaningful data—which smart brands are using to optimize everything about their business. Here's the big takeaway: the DTC movement is expanding beyond retail and goods to literally every single consumer market (i.e., consumer finance, real estate, transportation, home improvement—the list goes on). My fellow colleague, Riley, just published a great article about how the DTC movement is transforming financial services. Definitely worth checking it out for a deeper dive into this DTC shift.
  2. To echo Riley, companies who embrace this movement will thrive, while others slowly fade away. Intelligent use of data will distinguish the thrivers and faders, making it clear that AI/ML adoption is no longer a luxury—it's an absolute necessity.
  3. Here's my third and final takeaway: if your team ever plans a snowshoe expedition (which is probably just a Vermont thing) make sure to wear snowshoes that actually fit, or you'll end up tripping yourself constantly, as I did (Dad's gigantic snowshoes).

Regardless of your company's industry, we can all agree on one emergent truth: the future of consumer marketing requires AI/ML to stay relevant.




How Peacock Alley began their journey to an AI-driven growth strategy: an interview with Peacock Alley's Head of eCommerce and Digital Marketing

Perry McDermott on

Over the last 45 years, Peacock Alley has established itself as a leader in high-end, luxury linens and bedding by placing their valued customers first, from product design to enjoyable, evolving shopping experiences.

Peacock Alley recently signed on with Faraday to leverage artificial intelligence and nationwide consumer data to continue to deepen their understanding of their current customers and intelligently target and acquire new customers.

Ryne Higgins, Head of eCommerce and Digital Marketing, spearheaded the efforts to incorporate AI into Peacock Alley's marketing strategy. We had a chance to speak with Ryne about Peacock Alley, their decision to implement an AI solution, and what their onboarding experience has been like so far.

We'd like to thank Ryne for sharing his thoughts and experience, and hope you enjoy the interview!


Peacock Alley AI Interview

Can you provide a brief history on Peacock Alley?

Ryne:

"Our founder, Mary Ella Gabler founded Peacock Alley in 1973 (yes, we are 45 years old and working with an AI / machine learning software!) on the "Little Black Dress" theory to bedding and bath linens; own the best basics and then thoughtfully work everything else in.

About 9 years ago, she handed the reins over to her sons – Jason and Josh - and they are continuing to run the business today with her watchful eye still on product development and brand.

The company has been through a lot of iterations throughout the years but our core business channels are perhaps not that much different than you'd expect – we have a growing wholesale, retail, and eCommerce presence still today."

Who is a typical Peacock Alley customer? Is your customer base changing?

Ryne:

"The typical Peacock Alley customer is a difficult question and one of the reasons why we have paired with Faraday.

Across our channels, you may get a lot of answers. For example; our wholesale channel sells to a number of specialty stores, online dropship channels, and direct-to-designer. Our retail stores, while open to the public, mostly focus on the professional, accredited designer who is looking for the touch and feel experience in Dallas, Austin, Atlanta, or Nashville.

For my purview of the business (eCommerce), we are mostly focused on striking the cord with the do-it-yourself designers (think of what you see on Pinterest and beyond), whether they need coverlets and bedspreads, bath towels, or luxury fitted sheets.

I wouldn't say that our customer base is necessarily changing – we're still committed to the people that have made us successful over the past 45 years – however, as a brand, we are always interested in understanding what makes our customers tick and finding ways to attract new customers."

What does a typical Peacock Alley customer lifecycle look like? For example, are a lot of your customers repeat buyers? How do you communicate with past customers?

Ryne:

"Like a lot of 45 year old brands, our changes in the online space have been more revolution vs. evolution. In the past year; we've redesigned / replatformed our website, paired with companies like Faraday, and have really been trying to reshape our marketing mix between traditional and digital channels. For digital channels, we are seeing a high rate of new customers as we've built an experience that they are interested in interacting with.

We see very strong customer loyalty and to be frank with you, our product and brand has really stood on its own in bringing customers back historically. Our messaging and retention strategies have really been based more on the personal relationships we've built with our customers over the years.

As a brand with high-touch customer service and interaction, we are always looking for ways to supplement the old-fashioned "how are you doing" with digital communication that adds value to our customer's experience with the brand."

How has your marketing strategy evolved over the last 5 years? Where have you found success? Where have you struggled?

Ryne:

"Without getting into too many details, I will say that it is definitely in a place of evolution. Our business was built on the wholesale channel and sales tools, swatchfolios, etc have always been a staple of our marketing efforts.

That is still true today but we are also trying to find ways to improve those assets while also mixing in digital marketing (be it SEO, paid search, paid social, etc). As with most traditional media efforts, tracking can be difficult compared to the relative ease of digital. Faraday's toolset will allow us to continue to close that gap."

To what extent has data guided your marketing strategy throughout that period?

Ryne:

"Data and the ever-evolving digital landscape has been paramount in our evolution of our marketing strategy. When Mary Ella started the business, you could have never imagined directly tying a dollar spent to a dollar earned in marketing.

As these tools and technologies continue to evolve, for us it is about finding ways to marry the digital tools out there today with the traditional efforts that have really built and grown this business over the years."

Can you describe your current tech stack from your e-commerce system to customer data management? Has this changed significantly over the last few years?

Ryne:

"Sure. The fun thing about digital is it is pretty easy to find out what tools and technology people are using so it's pretty much public information.

Last year, we made a transition from Magento to Shopify, we signed on with a tool that allows us to visualize the true color of a product without having to shoot our products in a dozen different colors, and have signed on data and machine learning partners like Faraday.

We believe that to scale the marketing efforts of a luxury business through digital – we had to have a partner that could help us solve for the black box of channels like Facebook and Instagram.

It is pretty unbelievable that, with as great of a platform some of these channels are, they can only build look-a-like type prospecting audiences with 2.1M+ people in them, making it very difficult to understand why something is performing or not.

By leveraging a partner like Faraday, we have the ability to pull back the curtain and communicate with members of their account management, leadership, and theoretically their engineering team if ever needed.

For us to make significant adjustments in our marketing budgets, we need the ability to find the right people and send the right message at the right time. It is a fairly cliché statement but partners like Faraday should help us close that gap."

Prior to learning about Faraday, had you considered leveraging AI in any aspect of your business? If so, how? If not, why?

Ryne:

"I mean, sort of? I come from a background that is extremely digital in nature and I'm constantly trying to follow the trends that will help us build our brand. I will say – before talking to Faraday – I didn't think that AI was accessible to brands like ours quite yet (we have a small, scrappy team).

I was extremely impressed with what a relatively small team in Vermont can produce, and I liked their ability to "flex" their messaging to someone who considers themselves digital savvy but would have never considered scaling an in-house data science team in the short-term."

Why did you choose to leverage Faraday's AI solution?

Ryne:

"I've said a lot in the rest of the interview that I think answers this question but I would also say that the ability to take our use cases and personalize their product to what we needed to accomplish was key.

The Faraday team (shout out Robbie) is the type that listens, and I genuinely got the feeling that, in a world of technology partners who say a lot, they actually had the ability to walk the walk."

Can you describe your onboarding experience with Faraday?

Ryne:

"I've been through countless onboarding meetings and they are often met with a disconnect between sales and account management. It seemed like sales and account management was in sync. They had communicated our efforts, asked for refreshers as needed, and without the need for constant follow up have been meeting the quick deadlines that we needed them to.

As a business manager, I'm constantly met with "how" or "why" type questions and the team has been very responsive and thorough. It really sets the stage for our entire engagement."

We're excited to be working with you! Do you have any other comments or suggestions you'd like to add for companies looking to get started with AI?

Ryne:

"This might sound weird from a customer of the company, but don't just sign up for AI because you'd like to say you work with an AI firm. Take the time through the process and see if you can link Faraday's AI solution to your business outcomes.

Consider your ability to execute with the platform. We've been waiting for the solutions that we think Faraday can solve for and it seemed like a great fit for our business."

Thanks a bunch, Ryne!

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