Understanding your customers is important to the success of any retail business, but it's crucial for multi-brand retailers. With multiple brands under one company, it's challenging to get a complete picture of your customer's behaviors and preferences across brands. Even with digital data, most retailers struggle to persist customer identity across domains from one brand to another.
All retailers have different target demographics, such as a women's clothing brand that has segments for youth, adult, maternity, and seniors. There’s often crossover, and for multi-brand retailers it’s a given. One brand may target women aged 34-54 with a six-figure income, while another is a discount shopping brand that targets males over 50. Understanding how these segments overlap helps you build a more accurate customer profile to use in targeting and personalization. Do customers from one brand also shop for your other brands? If so, which ones? And why?
Too often, the view of the customer in these cases is fragmented and disconnected. Every data point needs to be unified to collect meaningful insight and personalize customer journeys. In the data-driven retail landscape, creating a single view of the customer is essential for businesses to not only stay competitive, but thrive. By capturing and integrating data from various sources (such as web analytics, purchase history, and loyalty program data), retailers gain a comprehensive understanding of each customer's behavior and preferences. This enables them to personalize the shopping experience across domains, increase customer retention, and drastically improve marketing effectiveness.
Fragmented data is the enemy of multi-brand retailers.
Organizations often have data siloed across different departments, platforms, and systems, which makes it challenging to create a unified view of each customer. For multi-brand retailers this is multiplied across the different brands, resulting in multiple profiles for a single consumer. Every new site visit is a new identity, even if it came from a hyperlink on a sister site. For example, did you know that amazon.com and smile.amazon.com would generate two different identifiers, and therefore profiles, in most systems?
So, why is this the case? Many retailers use Customer Data Platforms (CDPs) and other third-party identity solutions to collect and analyze customer data. However, these platforms are limited because they can’t track customer identity across different domains. So, when a customer navigates from one website to another, they get a new ID, and a new profile is created. Even worse, those profiles take a lot of time and resources to connect (if they ever are), which eliminates the possibility of live-time personalization.
The deprecation of third-party cookies further limits what retailers can easily determine about visitors landing on their websites. Brands can’t rely on third-party cookies to connect an individual’s interests and preferences across the web – or across their own sites. This means the ability to see when a customer navigates from a low-cost brand to a mid-range brand is gone. The invaluable insight of compiling data across those brands to get a deeper understanding of customer behavior and preferences is lost. But, with first-party data, retailers can connect those dots to build a comprehensive identity profile with deep understanding of the intent signals and buying habits of every individual. And, leveraging first-party data is much more controlled, compliant, and leads to stronger trust with consumers.
Identity resolution is critical to overcoming fragmented customer data.
The first step in solving the identity challenge is to capture and connect cross-domain data in a centralized identity profile or graph. In a modern data solution advanced algorithms and machine learning techniques collect the full story the data is telling and link it together to establish a single customer view.
This type of comprehensive identity resolution helps retailers overcome the challenge of data fragmentation by leveraging first-party data capture, which fills in many of the gaps left by the loss of third-party data. Connecting this data in live-time across channels, domains, and devices delivers unparalleled insight to drive acquisition and retention strategies.
With accessible, live-time data, retailers can identify customers (and anonymous visitors) even if the customer is using different devices. This is especially important in today's mobile-first environment, where customers increasingly use their smartphones to browse and shop online but may also use another device (such as a tablet or laptop) to continue the journey or make the final purchase.
By identifying customers across different devices and domains, retailers gain a more comprehensive understanding of each customer's behavior, preferences, and journey which enables a personalized shopping experience that drives loyalty and conversions.
Understand the customer journey and act on cross-domain insight.
Once your data is connected across brands, channels, and devices, the sky’s the limit! With a full picture of the customer journey, cross-domain insights deliver the ability to analyze consumer behavior across brands to better understand their preferences and needs. The more channels, or brands, a company owns the better picture they can get by connecting the data in live-time. There’s huge value to brands in understanding customer interest and personalizing their experiences on a larger scale.
Here are just a few examples of how this game-changing insight can unlock the ideal customer experience:
Hidden audiences
Imagine you’re a multi-brand retailer with several brands targeting different demographics. One of these is aimed at women aged 45-50 interested in wellness and fitness. Another targets men of a similar age interested in outdoor activities. By connecting data across domains, you gain insight into how these different segments interact with each of the brands, where they intersect (if at all), which channels are most effective, and what drives their behavior.
Through this analysis, you may discover many customers who purchase from the women's wellness brand also engage with the men's outdoor brand. This could indicate a segment of shoppers purchasing clothing for their husbands, teenage sons, or others. By understanding this crossover behavior, you can tailor your marketing strategies and product offerings to better serve these customers and increase loyalty. For example, tying the loyalty programs together or delivering cross-brand promotions.
Customer intent
You may also realize a particular segment of customers frequently buys high-end clothing from one brand but purchases low-priced accessories from another. By connecting this data, the retailer can infer the customer values quality in their apparel but prefers to save money on accessories. This insight can be used to personalize promotions and messages to customers, providing discounts on high-end clothing or suggesting lower-priced accessories that still meet their quality standards. Think about the impact of presenting a complementary accessory recommendation from the lower-priced brand while a visitor is on the high-end site shopping for clothing. That’s the kind of personalization that shows customers you truly understand their needs and value their business.
Build lasting customer loyalty
To ensure long-term success, retailers must prioritize customer loyalty by following their journey as they evolve and move into different target segments and brands. By doing so, they can build a more complete understanding of their customers, tailor their marketing strategies and product offerings, and ultimately increase customer loyalty.
For instance, if a customer who previously bought items from a brand targeting younger demographics transitions to a brand that caters to more mature customers, the retailer can adjust their marketing approach and product offerings to suit this new segment, fostering continued loyalty.
Better yet, retailers can also use customer data to anticipate their evolving needs and preferences - offering personalized products and services, at the perfect moment, in each stage of the journey. Let’s think about how this works: You’ve done a great job with your loyalty program and know your customer’s age range. They’ve been a regular purchaser of your trendy youth line for years, but thanks to robust customer profiles and data insight you know they’re approaching the demographics of another segment who purchases your trendy professional line. You can start to introduce this line gradually, building awareness right before they need it – so the moment they do, guess which brand is front-of-mind? Or, let’s say you’ve got several stores ranging from clothing to home goods, and thanks to cross-domain identity resolution you know that one of your clothing customers just created a baby registry. Not only can you present a special offer as a thanks for being a valued customer, you can also start delivering promotions for your maternity line. Did we mention the possibilities are endless?
By prioritizing customer loyalty and adapting to their evolving needs, retailers can foster stronger relationships with their customers, achieve sustainable growth, and ultimately establish themselves as a trusted and preferred brand.
The future is built on a single view of the customer.
Creating a single customer view is no longer just a competitive advantage – it’s a necessity. By leveraging first-party data and identity resolution tools to connect data across domains and make it accessible through a centralized platform, retailers can fully understand each customer's unique behavior and preferences. This unlocks valuable insights that can be used to personalize the shopping experience across channels, brands, and devices.
In marketing, timing and relevance are crucial to success. Presenting the right offer to a consumer at the right time (while the visitor is still engaged with the brand) results in instant rewards for both the retailer and consumer. Offers can extend beyond a single brand's website and encompass all the brands owned by a company. This approach enables multi-brand retailers to leverage the power of their collective customer data and deliver personalized offers to consumers across multiple touchpoints. By doing so, you create a positive experience for consumers and increase the conversion of potential customers into loyal ones.
