Artificial intelligence is transforming the way businesses understand their customers. Today, companies can use AI to collect and analyze vast amounts of qualitative and quantitative data and extract important insights into consumer behavior. However, it is the companies that effectively act on these insights that can derive competitive advantage.
“Just having data and insights available doesn’t make you data-driven,” said Sona Avarian, partner and global lead for the real and luxury sector at technology-enabled data science consultancy Ekimetrics, at a conference last week. Speaking at the BoF Professional Summit: New Frontiers. : AI, digital culture, and virtual worlds.
“How companies need to evolve their decision-making processes, the incentives that data provides, and their organizational structures to have real impact and move from using data to improve the status quo to leveraging data to truly transform.” We need to think about whether there is.”
Founded in 2006, Ekimetrics pioneers the use of AI and advanced data science to help brands optimize marketing dollars and leverage knowledge of customer preferences and behaviors to put customers at the center of business strategy. We have supported you. Ekimetrics works with The Estée Lauder Companies, Nestlé, and more than 50 luxury and luxury brands, and gathers insights from partner platforms such as Amazon, Meta, TikTok, and Google.
First, consumer expectations are increasingly focused on personalized experiences. However, in trying to achieve this, many companies lose sight of their strategy and focus solely on software as a service (SaaS), flattening the effectiveness of a service approach to personalization in a competitive environment. It's gone.
“Everyone is leveraging the same platforms and methodologies, so you end up leveling the impact and having to look elsewhere to be more competitive,” Avarian added. Ta.
Brands that consider customer centricity in every aspect of their business operations, from brand marketing and communications to product design, merchandising and planning, to financial operations and forecasting, are better able to reach their target consumers. It's been a huge success. This approach is achieved through access to and analysis of more primary data about customers, which helps management understand how to achieve and grow long-term business health KPIs, such as lifetime value (LTV) covered by Ekimetrics. You will be able to better identify areas of your business to optimize. White Paper, The Role of Customer Analytics Across the Value Chain.
In this issue, BoF speaks with Sona Abaryan, partner and head of global retail and luxury sector at Ekimetrics, on how companies can put customer data at the center of decision-making and leverage insights for short-term customer growth. I would like to share key insights from my talk at the BoF Professional Summit with Mr. Long-term return on investment (ROI).
What does it mean to be customer-centric today?
Simply put, [companies] We try to learn from our customers. No other industry is as competitive as the fashion industry. The way to stay ahead or catch up with the competition is to stay on top of how your customers are evolving.
Make no mistake, being customer-centric means more than just personalizing your emails and online catalogues. Indeed, this relentless “SaaSization” of personalization over the past decade has created a disconnect between strategy and tactics. Because everyone is using the same platform and methodology, you end up equalizing the impact and need to consider alternatives. To increase competitiveness.
How difficult is it to make good use of data today?
There's a lot of enthusiasm and ambition to be data-driven at the C-suite level, but while every company is different, some don't know where to start. Some of them don't know where the value lies or focus on a single use case rather than what is needed end-to-end to drive and impact adoption. Additionally, executives need to realize that having access to data and insights does not actually make them data-driven.
How companies need to evolve their decision-making processes, the incentives that data provides, and their organizational structures to have real impact and move from using data to improve the status quo to leveraging data to truly transform. You need to think about whether there is.
For example, we're working with L'Oréal on a product called Consumer Loop. The product uses artificial intelligence to analyze ratings and reviews at scale after a product launches. Consumer Loop makes that information available to product teams to enhance their product, research, and development strategies. [Now,] What was once a time-consuming and expensive process is now accessible to thousands of stakeholders around the world, allowing product decisions to be made quickly.
How can businesses optimize data insights to improve customer lifetime value?
Customer acquisition can be a costly process if you don't get the right customers and they don't end up returning. We believe that customer lifetime value is an important metric from a business perspective. How can you make the most of first-party data signals to help you predict early on whether a customer will become valuable?
Understanding how your customers evolve is critical to extending their longevity. If it works, we probably won't need to revive the brand every 10 or 20 years.
How are you thinking about your data collection strategy? You need to think about how to facilitate the login experience online so you can get more pre-purchase signals and signals in between to understand customer value. there is.
How can you use these customer insights to grow your business?
From a retention perspective, it's important to understand customer potential early on, which is critical information for client management. This gives customer relationship management teams the confidence to invest early in customers they know have high potential. This means you can use some of the more expensive channels because you know the value will be realized.
When it comes to acquisition from a tactical perspective, whether it's sending out a lookbook or inviting people to an event to ensure value is realised, media platforms can help you discover and target similar customers to your high-value customers. provides various ways to do so. When you look at things like marketing mix modeling, you can understand on a more collective level what marketing levers are there to help you acquire high-value and low-value customers.
What other benefits can your organization gain by taking a more customer-centric approach?
Let's start with your product strategy. The industry has historically seen a data-driven or customer-centric vision at odds with a design or product-driven vision. But whether you're a trendsetter for your brand, capitalizing on trends, or a mix of both, understanding how your customers evolve is extremely important to longevity. It is important. If it works, we probably won't need to revive the brand every 10 or 20 years.
For example, we worked with a fashion retailer who wanted to understand style from the customer's perspective, rather than as predetermined by the product team. So we looked at the combinations of materials, colors, fit, and lengths our customers were purchasing. Layering LTV on top of that can be very helpful in identifying which product ranges to expand or minimize to attract and retain high-value customers.
How can AI help measure brand marketing effectiveness and return on investment?
brand marketing, [including] Things like sponsorships are hard to track or definitely don't have the same traceability as ROI [to which] CFOs and CMOs are very familiar with performance marketing strategies.
The end of cookies certainly shook up the measurement space, but the biggest challenge was that attribution-based techniques were being used to make unrelated budget allocation decisions. So, if you've trained your CFO on seemingly high ROI, how do you incrementally increase that seemingly lower ROI and bring that number back up to what you need for brand investment?
If you have to make big budget sacrifices, think in a holistic way. Having one language of performance is important to maintain a level playing field in decision-making.
The challenge is not just for CMOs. His CMO these days has many silos within the business and many tools that provide conflicting recommendations. There's this attribute of “spending all your money on performance media,” and at the same time, you have all the brand and customer goals to achieve, but no real measurements to make it happen.
Sponsorship is a great example. The industry is now working together in support of sports sponsorship. But what is his ROI outside of the products sold? What has it done for your brand? What has it done for your sales? Sponsorships are one of the biggest blind spots in brand investing today without the right metrics and measurements.
What advice would you give to business owners looking to implement AI-powered insights into their businesses?
First, I think it's important to focus on increasing ROI and educate CFOs about it. We talk about measuring against multiple KPIs, not just short-term performance or marketing plans. Managers should consider how this will increase brand value. And how does it drive strategic customer objectives?
Finally, if you have to make big budget trade-offs, think in a holistic way. To maintain a level playing field in decision-making, it is important to use a single language to describe performance, following the analogy of sports sponsorship.
This is a sponsored feature paid for by Ekimetrics as part of the BoF partnership.
