Founder and CEO of FindMine Michelle Bacharach joins "Forbes Talks" to discuss her company, which uses AI in the retail space, and her thoughts on AI over the past decade.
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LifestyleTranscript
00:00 (upbeat music)
00:02 - Hi everybody, I'm Brittany Lewis with Forbes.
00:05 Joining me now is Michelle Bakarach,
00:07 founder and CEO of FindMine.
00:09 Michelle, thanks so much for joining me.
00:10 - Thanks for having me, Brittany.
00:11 - Of course, and before we dive into the conversation,
00:14 can you explain what FindMine is?
00:17 - Yeah, so I think like most founders,
00:19 I started a company to solve my own problem,
00:21 which is that I'm not the most stylish person,
00:24 I don't have an eye for interior design,
00:26 I don't know how to do a smoky eye,
00:28 and I found that when I would walk by a window display
00:31 in a retail store, I would be like,
00:33 whoa, yes, this, all of it,
00:34 that's my aspirational life, right?
00:37 And I feel like a lot of consumers have that struggle,
00:38 so I started asking brands and retailers,
00:40 like, why don't you just do that for every product you sell?
00:43 And what I found is that, you know,
00:44 there's just not enough resources in the world
00:46 to do a window display for every single thing
00:48 that most retailers and brands sell,
00:49 so they get about 5% or 10% of the product catalog
00:52 into those inspirational moments,
00:54 and then consumers like you and me are sort of left
00:56 without that for everything else.
00:58 So what FindMine does is we apply artificial intelligence
01:00 to deeply understand sort of the brand's creative vision,
01:03 so we can do that inspiration for every single product
01:06 in the catalog, and the consumer gets more of that
01:08 more of the time.
01:10 - I wanna read some numbers.
01:11 WWD reported that FindMine raised nearly $9 million
01:15 in Series A funding, bringing the total raise to 17.6 million
01:20 so first, a big congratulations,
01:22 but second, the company was founded in 2014,
01:25 this was a few years before the generative AI boom
01:28 of late 2022, so how did you get investors on board so early?
01:33 - Great question, and I think that like,
01:35 this fundraising round that we just did
01:37 was like the easiest I've ever experienced,
01:40 partly because I've been beating the drum for AI
01:42 for 10 years, and a lot of times people would be like,
01:46 cool, but like, what's the market for this?
01:48 Or cool, but I don't really understand it.
01:50 And so now the fact that we are here in this moment
01:53 and the market's fully developed for it,
01:54 people are like leaning in to AI,
01:57 and the fact that we kind of grew up on this old school,
02:00 if you will, style of discriminative AI,
02:04 which is really about like, taking the data
02:06 and to understand what it means,
02:07 and then blended that with the generative side,
02:09 which is really about producing something
02:11 that is typically done by a human,
02:13 is really how we crack the nut on getting that right blend
02:16 of AI to really deliver high quality results for what we do.
02:20 - That's really interesting that you saw this coming
02:23 a decade ago, but did you expect to see AI
02:26 where we are now then?
02:29 - I think that, I mean, it's obviously changing
02:32 every single day, and I have this reputation
02:35 in my own company of being like AI skeptic,
02:38 because I keep having the worst possible user experience
02:41 every time I ask ChatGPT to answer something for me.
02:44 So this is a running joke,
02:45 I'll screenshot it and send it to everyone.
02:46 So I'm constantly being surprised by what AI can
02:49 and can't do in this moment,
02:51 and I think that if we would circle back to 10 years ago,
02:54 and I forecasted what the future might look like,
02:57 I think there was maybe one or two things that I saw
02:59 that actually came to fruition,
03:00 and then everything else has just surprised me
03:02 and will continue to do so,
03:03 just given the pace of change in AI.
03:06 - AI has touched really every industry from education,
03:09 obviously now fashion, how has it impacted retail overall?
03:14 - Great question, so for our customers
03:16 who are predominantly like Fortune 500 brands,
03:21 they might be internet retailer top 500 type customers,
03:24 so they're big companies, they have lots of scale.
03:26 What we're doing for them is we're getting $89 million
03:29 in incremental revenue, because we're inspiring
03:31 their customer, the consumer more frequently,
03:34 which is causing brand loyalty to go up.
03:36 So we're actually seeing that customer come back
03:37 and buy again more frequently.
03:39 They're coming back for one of our top 500
03:42 internet retailer companies 8% more frequently.
03:44 So that repeat purchase effect
03:46 is building a more loyal customer.
03:48 And the impact of that really can't be understated
03:51 in an industry where people are sort of like,
03:54 you buy once from that brand and then never again.
03:56 So the financial impact is very real,
03:58 but then also the sort of, just what you can do with AI
04:03 when you don't have limitations of hours in the day,
04:05 or people getting tired, or all that stuff
04:08 just unlocks this whole world of possibility.
04:10 And in retail in particular, there's so much data.
04:13 Think about how many products, how many customers,
04:16 how many data points, products go in and out of stock,
04:18 everything changes.
04:19 That's a blessing and a curse when you talk about AI.
04:22 - FindMine is fashion focused.
04:25 And when you're talking about,
04:27 hey, maybe I wasn't the most fashionable person,
04:29 when you said that at the beginning,
04:31 that really resonated with me.
04:32 I don't know how to do a smokey eye either.
04:34 I don't have an eye to put everything together.
04:37 So the product resonates with a lot of women.
04:40 AI, as we know, is a very male dominated field.
04:44 So how did you get investors to come onto this?
04:47 And was it harder, especially as a woman,
04:50 going into a male dominated field?
04:52 - Great question.
04:53 I definitely feel like I had the push and pull
04:56 because fashion is female dominated.
04:59 And we do beauty and home,
05:01 and those tend to be spaces where there's just more women,
05:03 maybe not at the leadership levels
05:05 as much as they should be.
05:07 But then we have also the AI side,
05:08 and our AI technology is very, very deep
05:10 and very, very robust.
05:12 So I kind of had to play both sides of it.
05:14 And I think one thing that really helped me get investors
05:17 excited in this round in particular
05:19 is the length of history we have.
05:21 Because there's so many companies coming in
05:23 that are, you know, FindMine's AI first
05:25 and use case specific,
05:26 and I think that's a big differentiator.
05:28 There's so many companies coming in
05:29 trying to solve something in retail,
05:30 trying to solve styling,
05:31 and then bolting on AI on top of it.
05:34 It's just not differentiated.
05:35 And so if you're an investor putting money in,
05:37 it's like, well, anyone has access to these technologies,
05:39 how do I know you're going to be the one to succeed?
05:41 The fact that we have proprietary
05:42 and very deep data sets on what we do,
05:45 I think just put us kind of to the top of the list
05:47 and helped overcome some of that, you know,
05:49 there's just less people looking like me in this field.
05:53 >> Let's talk about that a little more,
05:55 because as we know,
05:56 AI has disrupted industry after industry
05:59 over the last year and a half.
06:00 So how does FindMine differentiate itself in this field
06:04 aside from the longevity?
06:06 >> Great question.
06:07 So the first thing is that
06:08 there's kind of these two camps within AI,
06:10 discriminative and generative that I mentioned before.
06:12 So the discriminative stuff is sort of more old school,
06:15 and then the generative is like kind of the new shiny object.
06:18 And we believe that you need both
06:20 in order to succeed in this particular pursuit,
06:22 which is styling.
06:23 The reason for that is,
06:24 if you think about generative AI
06:26 and the big players in the space,
06:27 Google, Amazon, Meta, et cetera,
06:30 you can ask it, hey, make me a style guide,
06:31 make me a lookbook, right?
06:33 And maybe you're Abercrombie.
06:35 And if you ask it that,
06:36 it might give you something that looks like American Eagle.
06:39 That's a really scary place for brands to be
06:41 'cause they want to differentiate from each other.
06:43 They don't want to look the same.
06:44 And so this generative AI
06:46 that is trained on sort of the wisdom of the crowds
06:48 collapses the differentiation between those brands.
06:51 And that's exactly what FindMine solves.
06:53 To solve that,
06:54 we have to use that discriminative side of things
06:57 to deeply understand brand.
06:58 We actually map brand in multidimensional space,
07:02 which is a crazy thing to kind of picture.
07:04 But being able to articulate what is brand to an AI
07:08 using computer speak, using vectorization,
07:11 is the way we're actually able to then tell generative AI,
07:13 make me a lookbook that looks like Brand X
07:15 and have it actually look precisely like Brand X.
07:18 - Can you dive a little deeper in there?
07:20 How are you distinguishing brand to brand?
07:23 Because when you think of Abercrombie and American Eagle,
07:26 they have similar looks.
07:27 So how are you breaking those down?
07:29 - Yeah, so as a consumer from the outside,
07:31 and we don't work with either of those,
07:32 I'm just using them as examples here.
07:34 You can see that they're similar in some ways,
07:37 and you maybe get a sense of how they might be different,
07:39 but maybe not.
07:39 And that's kind of where you stop thinking about it, right?
07:42 'Cause you're a consumer,
07:42 you just kind of move on with your day.
07:44 If you work for either one of those brands,
07:45 if you're the creative director of either of those brands,
07:48 they can rattle off a whole bunch of ways
07:50 that they're different.
07:50 But they also don't have the vocabulary
07:54 to describe in human language
07:56 exactly what is specific and unique about each of those.
07:59 So if they were to crack open OpenAI
08:02 or Stability or any of these kind of LLM technologies
08:06 and try to teach it what their brand is about,
08:08 what ends up happening is all the promise of time savings
08:11 that generative AI is here to tout,
08:14 you end up losing,
08:14 'cause you have to torture yourself into a pretzel
08:16 to try to explain to it what is it about your brand.
08:19 And that's really the thing
08:20 that FineMind has become uniquely good at,
08:22 is to very quickly get a sense of what it is to mean,
08:25 what does this brand mean, basically,
08:27 and then feed it into all these different models
08:29 for the different outputs that look high enough quality.
08:31 - Meta, as I'm sure you know,
08:33 is coming out with smart Ray-Bans
08:36 that provide outfit inspiration.
08:38 So how does FineMind differentiate itself
08:42 from those types of products?
08:43 - Yeah, so first of all, we're not competing with Meta.
08:46 That's sort of the wisdom of the crowd's styling response,
08:49 which has its place in time.
08:50 Wearing and getting dressed,
08:51 I just wanna know, quick fit check, is this okay?
08:54 Am I gonna get laughed at in the mom's group
08:58 that I go to if I wear this, right?
08:59 There's a very specific purpose for that.
09:01 And then there's also the leadership and expertise
09:04 of an individual brand, which builds that loyalty
09:06 and helps you be a better version of yourself.
09:08 And so I see, potentially,
09:10 when brands start flooding into that space,
09:13 trying to say, okay, Meta,
09:14 suggest my brand, suggest my brand.
09:16 There's a bidding environment or a retail media
09:19 or advertising ecosystem built around that recommendation
09:22 that you get in that lens.
09:24 That's where FineMind can come in,
09:25 because we can say, all right,
09:26 well, don't just push this specific product
09:30 for any old reason.
09:31 Push what's important to the brand
09:33 and style it in a way that is authentic
09:35 to the creative direction of that brand.
09:36 So you're getting the brand's point of view,
09:38 not just the wisdom of the crowd's point of view.
09:40 - Speaking of paradigm shifts,
09:41 we have seen a shift in the way people shop
09:44 with the rise of social media, particularly TikTok.
09:47 I know some of your clients include Lululemon
09:49 and Vineyard Vines.
09:51 They both have a large TikTok presence.
09:53 Are they nervous, apprehensive about a potential TikTok ban?
09:57 - I think a TikTok ban is a blessing and a curse
09:59 when you think about what brands are gonna feel about it.
10:02 On the one hand, obviously, there's tons of traffic
10:04 and sources of revenue that come from that channel.
10:08 But on the other hand, there's also a leak
10:10 from the brand's sort of core properties
10:12 to a place like TikTok,
10:13 because we talked about it earlier,
10:15 the scale issue of trying to inspire your customers
10:18 for every single product.
10:20 If I go to buy this blazer
10:22 and I don't see it styled in a lookbook
10:24 or I don't know all the different outfits to wear with it,
10:26 guess where I'm gonna go?
10:27 I'm gonna go to TikTok or Instagram
10:28 or one of these places and just put in
10:30 thick blazer, thick white blazer,
10:33 and just see what kind of inspiration I get.
10:35 And that's really an opportunity for the brand
10:37 to reclaim that expertise in that moment
10:40 and then sell the customer the jeans and the shoes
10:42 and everything that goes with it.
10:44 So that's kind of the blessing side of it.
10:46 And then I think all the brands that we work with,
10:48 they're all kind of thinking about user-generated content.
10:50 They're all thinking about influencers
10:52 and how they can capitalize on the kinds of consumers
10:55 who don't necessarily want the brand
10:57 to tell them exactly what to do.
10:58 'Cause I think all of us as consumers,
11:01 we want expertise from the brand sometimes,
11:03 we want it from our friends sometimes,
11:04 we want it from influencers sometimes,
11:06 we want it from non-celebrity people
11:09 who are just like us sometimes.
11:11 And so you kind of have to cover
11:12 all of those different bases
11:14 to give the customer everything that they need.
11:16 So I think it's gonna be both a blessing and a curse
11:18 if TikTok does get a ban.
11:20 - I know you have been embracing AI for a decade,
11:24 but do you think if a company is not embracing AI overall,
11:28 they're being left behind in this space right now?
11:31 - I think it's still early days.
11:32 I think there's plenty of time to get your feet wet.
11:35 I liken this to sort of the beginning of the internet
11:38 or the beginning of using computers for stuff, right?
11:42 Now, if you say, "We use computers to do banking."
11:45 It's like, well, duh, you and everybody else, right?
11:48 That's how it will be to say,
11:50 "We use AI to do X in the future."
11:52 Maybe three years, maybe five years, maybe 10 years,
11:54 we don't know how long, but it's coming.
11:56 It's just such early days now
11:57 that if you don't, like, I hate to see companies be like,
12:00 "What's our AI strategy?
12:01 "We need to figure out how to bring AI in."
12:04 That's the wrong way to approach it.
12:05 It's what are our problems?
12:06 What is the strategy we're trying to solve for our business,
12:09 for our industry, for our customer?
12:11 And if AI can support you in getting to that goal,
12:14 that's a great application for AI.
12:15 But AI for AI's sake tends to always be a fool's errand
12:18 of a lot of money and a lot of waste of time
12:20 and a lot of frustration.
12:22 - Do you think AI in your case promotes brand loyalty?
12:27 - Yeah, absolutely.
12:28 I mean, one of the things
12:29 that I started the company based upon
12:32 is when I had a really great interaction
12:33 with a store associate or a beauty counter expert
12:36 or someone who really oozed the brand expertise,
12:40 I just found myself going back to that more often.
12:43 I can feel that part of my brain
12:44 almost like clicking into gear,
12:45 like this is one I trust,
12:48 versus when you buy a product
12:51 and you don't wear it right away,
12:52 or it doesn't quite ever fit into your living room,
12:55 and you're just like,
12:56 every time you look at that chair,
12:57 you're like, "I just don't know."
12:59 You question yourself, you doubt yourself,
13:01 but you certainly doubt the brand.
13:02 So if you can make the customer feel confident
13:04 with their purchases
13:05 and feel like they're living their best life,
13:08 it 100% does drive brand loyalty,
13:09 and we see that in the data.
13:11 - And what do you say to people who are more bearish on AI
13:14 who think, the first thought that comes to mind
13:17 when they think of AI is,
13:17 "Hey, is this going to take over my job?
13:20 "Is this going to take over the world?"
13:22 What do you say to them?
13:23 - I think that's a fair concern,
13:25 and I absolutely believe that the guardrails
13:27 need to be in place for things like rights issues.
13:30 You know, the SAG Afterstrike was really all about that.
13:34 Training on people's creative pursuit
13:35 to then disintermediate them from the process.
13:37 I don't believe that that's,
13:39 I believe that people are right to be concerned about that.
13:41 In FineMind's particular case,
13:43 we have to have the seed from the people.
13:46 The people are necessary but not sufficient.
13:48 They have to create that beautiful window display
13:51 and those, like, what is this season all about?
13:53 But they only do it, again, remember,
13:54 for five or 10% of the product catalog.
13:56 No one has the time and resources
13:58 when you're a multi-million dollar, a billion dollar brand
14:02 to create beautiful editorial moments
14:04 for every single product you sell
14:06 and then go back and update them
14:07 when this product went out of stock
14:08 and this one's come in and now there's a new trend.
14:11 There's just, the people to do that don't exist today.
14:15 So there's no jobs to disintermediate.
14:17 And then what we do is we cast the people
14:18 who are doing that work for that five to 10%
14:21 in this very elevated light.
14:23 Like, they're the creative directors,
14:25 they're the Anna Wintour behind the whole operation
14:28 and then we're just executing it.
14:30 We're just taking a baton and running with that.
14:32 - So you're saying, essentially,
14:34 we're not stealing anyone's jobs,
14:35 we're making your life easier.
14:38 - Making their life easier
14:39 and almost elevating what they do.
14:41 One of our investors is this woman who is,
14:44 she's just been in retail and C-suite
14:46 and kind of senior VP roles her whole career.
14:49 And the way she described it was,
14:50 you give me time back to do the part of my job that I love,
14:54 which is the deeply creative work.
14:55 It's really fun to create one outfit,
14:57 it's really fun to design a furniture set,
14:59 but it's really boring and tedious
15:02 to do the 15,000th one, right?
15:04 You max out super fast.
15:06 So like, let's let them do what they do,
15:07 which is creative and fun.
15:09 And then we just replicate it at scale and everybody wins.
15:13 - Can you talk about who are your investors?
15:16 What do they look like?
15:17 What are their backgrounds?
15:18 - Yeah, great question.
15:19 So we have a whole kind of running the gamut of investors.
15:22 And so who led our series A
15:24 was a company called Greyhawk Capital.
15:27 The partner is this guy, Brian Smith,
15:29 who is just a very pedigreed kind of Silicon Valley investor,
15:33 SaaS software, not necessarily retail, not necessarily AI.
15:37 He's a generalist SaaS investor
15:39 and just very disciplined in what he does.
15:41 And he saw two things.
15:42 He saw kind of the market opportunity for AI
15:44 and then just the roster of customers we have
15:47 paying us real money to solve a real problem.
15:50 And so that's kind of one camp of investors
15:53 is like the Silicon Valley VC type.
15:56 But then we have angels like the one I mentioned before,
15:58 her name is Sarah Wallace.
15:59 She's the COO at Minted,
16:01 which is a home design and furnishings marketplace.
16:04 And she came from Gap
16:05 and then she came from Walmart prior to that.
16:07 So the retail folks, I think really get it.
16:09 And then the AI folks as well.
16:10 We have some investors who are just,
16:13 they've been doing this for more than a decade.
16:15 They've been doing this for 20, 30 years
16:17 and really have seen the opportunity that AI has opened up
16:20 for a really big financial return
16:23 in the application that we've chosen.
16:25 - So you, along with some of your investors
16:27 have years and years of experience in AI.
16:30 What do you think's missing
16:31 from the national conversation then when it comes to AI?
16:33 Because there is this debate of,
16:35 A, this is really helpful.
16:36 This will move our society at breakneck speed.
16:39 This is a paradigm shift.
16:40 There's the other debate of people more scared.
16:43 Is this going to steal my job like we talked about earlier?
16:46 - It's such a good conversation to have
16:48 for any paradigm shift.
16:50 I mean, we had to have it around computers.
16:52 We had to have it around the internet.
16:53 We had to have it around social media.
16:54 There's so many good things that social media have done
16:57 for humanity and there's so many dirty, bad, awful things
17:01 that it has done and you can't paint it all
17:03 with the same brush.
17:04 So I think it takes a very disciplined
17:07 and time-intensive approach to have these conversations
17:10 that a lot of times I think that people who are involved
17:13 in the conversation aren't willing to take the time
17:17 to have that, right?
17:17 I'm talking about in Congress.
17:19 I'm talking about kind of like think tank groups
17:22 and stuff that talk about AI.
17:24 We're missing a lot of what we should be thinking about
17:27 and we're spending too much time talking about the things
17:30 we shouldn't spend so much time talking about.
17:32 It's tricky.
17:33 - Michelle, I appreciate the conversation.
17:35 Thank you so much and congratulations.
17:37 - Thanks again.
17:38 (upbeat music)
17:40 (upbeat music)
17:43 [BLANK_AUDIO]