The Data Activation Guide for Commerce

Data is the new gold. It’s how commerce teams gain a deeper understanding of customers, the driving force behind personalization at scale, and the fuel that powers AI and automation. However, a staggering 81% of business leaders struggle with data fragmentation and silos. The solution? Data intelligence. Simply put: Data intelligence refers to the tools and methods your business uses to gain insights from all the information you collect. It includes the technology you use to unify data, harmonize it, ensure that it’s trusted, and power the AI and applications you use every day.

This is what makes it possible, efficient, and cost-effective to build richer, more personalized digital experiences for your customers. At a time when 65% of customers expect companies to adapt to their changing needs and preferences, actionable data has never been more important. Data-driven companies outperform their competition: Their customers are more loyal, conversion rates are higher, and their teams are more productive.

So, how can commerce teams use data intelligence to propel business forward? Here’s everything you need to know about data intelligence tools and strategies to drive success.

Improving data use and management is a top priority for commerce leaders this year. That’s because at most organizations, fragmented data is trapped in silos all around the business. These data silos lead to duplicated efforts, overlooked insights, and disconnected customer experiences. By unifying all the data from across your business, you gain a more complete view of every customer, give business users a single source of truth, and make it much easier to uncover actionable insights.

Data intelligence platforms are pivotal for unifying, consolidating, and optimizing all your data. In essence, you can think of these platforms as the next generation of customer data platforms: They gather insights from various systems and touchpoints where data resides (such as business applications, web engagement and back office systems, and data lakes or warehouses) and craft them into a single, centralized view that encompasses both customer and business intelligence. But a data intelligence platform goes further than just visualizing all this data; It helps you streamline the journey from analysis to action. With an integrated platform, you can easily view comprehensive performance metrics, understand the underlying reasons for these trends, and power personalization workflows. Not only can you understand your business landscape, but you can also effectively implement data-driven strategies for improvement — without the need for painstaking manual analysis.

This consolidation paves the way for a single, cohesive source of truth across your organization. With unified data at your fingertips, you can leverage artificial intelligence (AI) and automation, powering marketing effectiveness, service excellence, and commerce efficiency. Aldo Secaida, VP of Solutions at Red Van , puts it this way: “AI and automation aren't just tools for efficiency; they're the architects of a new era of commerce where experiences are tailored in real-time.

Picture a system that provides a comprehensive view of customer behavior — no matter where the data sits. This means better employee engagement, enhanced productivity, and elevated customer experiences across sales, service, marketing, and commerce, ultimately driving deeper customer loyalty.

Imagine you had a 360-degree view of every shopper at all times. This means you could see the entire customer journey at a glance, with easy access to each customer’s profile information, product preferences, order history, channel engagement, and more. With this comprehensive data, you could create personalized, timely, relevant experiences that would increase conversions and customer satisfaction. It would become easier to win loyalty, quickly increase operational efficiency, and truly differentiate your brand.

With advanced data intelligence tools, all this becomes possible. You can centralize key performance indicators (KPIs) from across the business, uncover trends, and access actionable insights on a single platform.

Only 17% of customers fully trust companies to use their data responsibly. That said, it’s critical to build a trusted foundation as you collect, organize, analyze, and take action on your data. Here are a few considerations:

• Provide a clear exchange of value for data: Most customers (71%) are more comfortable providing data if they’re given a clear explanation of how it will be used. Be transparent about how customers’ data will improve their experiences and interactions with your business.
• Treat sensitive data carefully: Develop stringent security standards around data collection and use. You’ll need to answer tough questions, like: How do you ensure sensitive data is anonymized? If you use data to power AI initiatives, you will need to know how you will monitor accuracy and audit for bias, toxicity, or hallucinations.
• Choose technology partners wisely: Your commerce provider should assist you with compliance — from GDPR to CCPA. Secure design and implementation of custom code, sourcing, deployment, and maintenance of third-party integrations and extensions. Implement continuous monitoring and incident response on customer and custom third-party integration assets.

Personalization is now table stakes for commerce pros: A whopping 78% of business buyers and 61% of consumers expect companies to always understand their unique needs and preferences. However, only about half (53%) of digital leaders report being highly effective at using data to understand customers. So, how can businesses tailor shopping experiences to convert shoppers into loyal, repeat customers? The answer lies in unifying customer data and harnessing this information to drive automated personalization efforts.

One of the best places to start: automated product recommendations. Online shoppers who engage with a product recommendation have a 70% higher conversion rate, according to one study . Commerce leaders are taking note. To spark personalization at scale, beauty giant L’Oréal uses data from across its business to fuel tailored product recommendations and increase customer satisfaction. Based on real-time and historical data, L’Oréal can send consumers tailored suggestions and beauty advice automatically — wherever they prefer to shop. Barbara Lavernos, Deputy CEO puts it this way: “We’ve accumulated a century-long goldmine of data solely about beauty. Today, our ambition is to transform this treasure into the ultimate consumer beauty experience — while, of course, respecting data privacy.”

Expanding on this foundation, personalizing storefronts for different customer segments further elevates the shopping experience. For example, an outdoor apparel retailer might adjust its homepage display and product lineup based on a visitor’s previous interactions, showing more hiking gear to a customer who frequently purchases or browses related items. This strategy ensures that each customer feels uniquely understood from the moment they arrive at the site.

Personalization extends beyond product recommendations and storefronts to include tailored product descriptions and targeted promotions. By dynamically adjusting product descriptions to highlight benefits and features most relevant to each customer segment, and by personalizing promotions to reflect individual shopping habits and preferences, businesses can significantly increase engagement and conversion rates. This level of personalization not only meets but exceeds customer expectations, fostering a sense of value and loyalty that encourages repeat visits and purchases.

Personalizing the commerce journey is a key differentiator, especially for B2B companies. Today, 63% of business buyers say most customer experiences fall short of what they know is possible. Buyers expect the same level of personalization they get as consumers, but the added complexity and scale of B2B can make it difficult to deliver. That’s where data intelligence for B2B comes in.

The B2B buyer journey is intricate and often much longer than consumer sales. Data silos and fragmented systems can often complicate the process and keep key insights mostly hidden from marketers and sellers. But data intelligence helps your teams uncover data from relevant moments and fine-tune offerings and outreach. With consolidated, harmonized data from around your business, you can enhance lead-to-account mapping so sales reps only focus on the most qualified leads. You can also perform more intelligent journey stage mapping so you can personalize messaging and outreach for prospects’ specific needs.

Selling more efficiently is hard when the valuable data you need is dispersed in multiple silos across your organization. When teams are spread thin and being asked to do more with less, it’s even harder. Soumya Ghosh, Senior Director of Technology at Quest Diagnostics , puts it this way:

“Data points are buried all around your enterprise. Order management systems, customer service records, returns … If you want to learn fast and react quickly, a data platform can uncover those data points for you — immediately.”

By connecting commerce to harmonized data and intelligence, your team suddenly has access to game-changing, first-party data like browsing history, recent transactions, payment preferences, and product feedback. With those important insights, you can design intelligent and efficient commerce journeys that satisfy customers every step of the way.

No matter your role, data intelligence can help you increase productivity across your business.

• Merchandisers can access data from across your organization to help determine the right categories, sets, and product pairings to increase conversions and average order value. Activated with AI, merchandisers can set up automated alerts based on trending products, marketing insights, and shopper data. They can also digitize and automate manual processes.
• Operations and logistics teams can leverage data to align supply with demand. When your data intelligence is connected to inventory and order management systems, you can more accurately predict the demand of your goods and fully prepare for potential spikes that may impact fulfillment issues. This also helps you drive efficiency and avoid costly inventory mishaps like out-of-stocks, overstocks, mis-picks, and mis-shipments.
• Designers and developers can use first-party data from an intelligence platform to help guide their roadmap and determine which pages and innovations to optimize and prioritize. With a deeper understanding of every customer and how customers interact with your business, your commerce teams can validate their plans and make more informed decisions.

Ultimately, data intelligence helps your commerce team increase productivity, conversions, and customer satisfaction.

With customer acquisition costs higher than ever before , commerce teams need to be increasingly strategic about digital spend and initiatives. It’s critical to make the most of your resources and ensure that you’re devoting your efforts to optimizing the parts of the customer experience that will make the biggest impact. The solution: a deeper understanding of your customers. That’s where segmentation can help.

Every shopper is unique, and the same experiences won’t resonate with all of your customers. But when you segment shoppers into groups by interests, product preferences, geography, and service history, you can deliver tailored commerce experiences that are more relevant — and more likely to convert.

Start by categorizing prospective customer data based on common characteristics. For example, an apparel retailer could segment shoppers by purchase history, preferred styles, and chosen fulfillment method. Layering ecommerce data with browsing behavior, point-of-sale, and loyalty data gives you an even more complete view of your audience. Once you have a holistic understanding of what your target audience is searching for and where they might be looking for it, you can segment customers by lifetime value, create personalized email promotions, and tailor commerce site experiences.

For example, Erika McGrath, Vice President of Salesforce Data Cloud and MarTech Practice at Astound Digital , suggests that commerce teams determine which products drive new customers, and what your most popular second purchase items are. With these data points, your commerce team can come up with a plan to target first-time buyers with ads for products and categories that drive new customer acquisition. With segmented data that tells you the most used channels, payment options, and fulfillment methods for first-time shoppers, you can target your ads and promotions with more precision.

Not sure where to start? McGrath also offers this advice:

“Identify clear use cases that stitch together transactional, behavioral, and engagement data. Don’t let the project get too big, too quick. Start small to deliver immediate ROI, then add more data to your data model.”

A real-time data intelligence platform gives you the power to segment quickly and target new audiences more intentionally, driving down operational costs without sacrificing the “wow” factor that helps you build brand love.

The average company uses over 1,000 different apps to run its business, so an overwhelming amount of data ends up in siloed workflows. Connected commerce powered by data and intelligence is the key that will unlock success. As business priorities shift and customer expectations continue to skyrocket, it’s increasingly important to collect and activate real-time customer data and create hyper personalized experiences that will differentiate your brand.