Using AI to Create Customer Centric Business Strategies | The Business of Fashion

hi son good morning everyone as you've just heard for the last 17 years eim metric has been pioneering the use of AI in Advanced Data science in the luxury retail and many more Industries in fact

but son I want to kick off by doing away with the jargon and thinking about what does customer centricity really mean today and how are the organizations and companies that you work with what are

they trying to solve by becoming more customer Centric I mean in its simplest terms um it's about learning from the customer right we operate in an industry I think it's hard to think of any other

industry that has as much competition as fashion we have so much choice and so just to stay ahead or even to keep up with the competition Brands really need to have their finger on the pulse of how

that customer is evolving um and to be clear when we talk about being customer Centric it's so much more than you know that

personalized email um or the the online catalog um and in fact this Relentless statification that we've seen over the past decade has created a disconnect

between strategy and tactic and with everyone using the same platforms the same methods you end up kind of evening out the impact and need to look elsewhere to to drive a Competitive Edge

you mentioned everyone using the same platforms and that evening out of the impact but I think CMOS C cbos entire executive teams today are overwhelmed with a barrage of data how how

challenging do you believe it is today to use data effectively in decision-making processes um I think we see a lot of enthusiasm and ambition at the C Level

to to be data driven and obviously every company's is quite different but you know some of them don't know where to start some of them don't know where the where the value is or some of them think

of a single use case rather than what it takes and to end to drive adoption and make an impact um or you know they think that just making data and insight

available doesn't doesn't actually make you data driven and so Executives and and companies need to think about um how do they need to evolve their decision-making process the

incentives that they provide the organizational structure to to really make an impact and go from um you know just using data to improve the status quo to being really really

transformative with it and maybe to to give you an example of um we work with L'Oreal on uh a product called consumer Loop um

where um really it's about understanding how you can leverage uh we we leverage artificial intelligence to analyze ratings and reviews at scale after a

product has launched um and make that information available for for product teams to enrich their product um Improvement and research and development

strategy and what was previously a very um time consuming an expensive process uh is now accessible to thousands of their stakeholders globally and helping

them make faster decision about products I want to talk now about LTV it's obviously of high concern to everyone in the industry and we are you know now living in a very different data

environment to what we were previously and primary data signals that you know the data that you can drive in your own ecosystems have become much more important can you tell me about how

businesses can use or the best practices bus can can adopt in nurturing LTV in their customer bases I think you know we know that um acquisition of customers

can be an expensive expensive process if you don't acquire the right customers and they don't end up repeating and so we see customer lifetime value as being an incredibly important metric to steer

the business and so to your point you know the first question is how do you even maximize the first party data signals that you have to be able to predict early on whether the customer is

going to be high value or not so how are you thinking about your data capture strategy how are you thinking about you know promoting logged in experiences online so that you can have a lot of

that pre purchase signal and the in between signals to understand the value of that customer and how do you then use that to grow the business itself you know once you've understood the value what are the tactics available to

actually create some kind of impact in terms of retaining the customer early on um what this what this gives the CRM teams is the confidence to invest early

on in a customer that they know has high potential um and so that means you can use some of your more expensive channels because you know the value is going to be realized so whether it's you know sending them that lookbook or inviting

them to the event and making sure that that value is realized um when it comes to acquisition from a tactical perspective you know media platforms

provide a lot of uh ways that you can look for lookalikes of uh of your high value customers or at a more aggregate level you can look to things like marketing mixed modeling to

understand what are the marketing levers that really over index in helping you acquire high value customer versus a low value customer we've spoken a lot about marketing and obviously it's an

incredibly important element of our industry but there is opportunity to apply these insights across organizations perhaps you can highlight some of the the use cases across different companies

I think you know there's there's probably a lot of functions I could talk about but um if I talk about maybe product strategy as as one I think

historically the industry has seen um you know a datadriven or customer Centric Vision as being at odds with a really design and product driven Vision

but whether you are a trend Setter uh in terms of your brand or whether you capitalize on Trends or your some sort of mix of the two um

uh you know really understanding how your customer evolves is is critical for longevity and uh if you you know and if you do that well you know maybe you don't need to have a brand come back

every decade or two um to give you uh to give you an example we worked with a fashion retailer who really wanted to understand style from a perspective of their customers and not something that's

predetermined by the product team and so we looked at what was the the combination of you know materials of colors of uh of fits and length that customers were

buying and then once you overlay lifetime value on top of that it becomes really powerful in helping you identify what are the product ranges that you should extend because they are

attracting and keeping a high value customer and what are the product ranges that you should be minimizing we are Sly coming to the end of our time but I want to end on you know now I believe the end

of the cookies era is obviously something that we are all aware of the age of the cookie is over and The Business of fashion state of fashion survey recently found that 74% of

Executives plan to increase brand marketing expenditure and only 43% I think believe are going to increase Performance Marketing expenditure brand marketing traditionally was perceived as harder to measure and we were talking

about this yesterday with a number of people what's your advice in this space in terms of measuring the return of investments in brand marketing spaces that perhaps traditionally like

sponsorship like dressing are harder to to track or certainly don't have the kind of certainty on Roi that CFOs and CMOS have become very accustomed to with Performance Marketing strategies I think

um you know the end of cookies has certainly shaken up the measurement space but I think the biggest challenge was that attribution based methods were being used to make budget allocation

decisions that frankly they had no business to make um and so now you know if you've trained your C Foo on extremely you know seemingly High rois

how do you walk back that um that figure to you know what you need from Brand investment with incremental rois that are going to seem like they're lower um

and you know the the challenge isn't just that for Cosmos I think they have a lot of silos in the business these days and a lot of tools giving them conflicting recommendations so you have

you know attributions saying pump all your money into uh into performance media and at the same time you have all these brand goals to achieve and customer goals to achieve and no real

measurement to do that and you know sponsorship is a is a great example because you know we I even read that in the bof that you know the industry is

really kind of uh uh aligning behind Sports sponsorship you know it feels hot it feels right but you know how many of you can tell me you know what the ROI of that is beyond some merchandise that

that you've sold what has it done for your brand what has it done for for your sales and you know I think sponsorship without the right metrics is probably one of the biggest blind spots in

measurement these days absolutely sonor thank you so much is there anything you want to share to close the session I think I had three tips um which are on the next slide if we ever get to them um

I would say first is you know focusing on incrementality is really key and educating your SE Suite on what the difference is between that and attribution and how that should be used

um you know we talk about measuring against multiple kpis so not just what your short-term performance of marketing is but how does that how does that drive

your brand Equity your your full funnel and how does that drive your your strategic customer goals and finally um really thinking about it in a holistic

way when you need to make tradeoffs of big budgets um you know it's important to have one language of performance so you can you know to keep the with a sports sponsorship analogy keep a Level

Playing Field of of that decision making donor thank you very much for all of your insights if you're interested in learning more we'll be writing up the conversation we heard yesterday so look out on bof but thank you all for your time