Why Retail Marketers Must Adopt a Data-First Mindset to Succeed in The Omnichannel Age

With the world of retail continuing its trajectory towards “nearly normal”, brick-and-mortar foot traffic is returning with a vengeance as consumers flock back to physical stores for the in-person shopping experience they craved during the pandemic lockdowns. But they are no longer the same consumers they were before. With retailers forced to adapt by leveling up their online operations, consumers were introduced to new shopping options, becoming a lot more digitally savvy than ever before. As a result, it is now dawning on everyone – brands and consumers alike – that shopping has changed forever, and marketers must adapt to a new, post-pandemic breed of customer who is an online-offline omnichannel hybrid.

The evolution of the modern marketer

About a decade ago, marketers were typically thought of as “creative types” responsible for ‘little more’ than creating content, managing social media accounts and running basic SEO optimization, ads and promotions. Even then, this warped perception was testament to how little those who didn’t work in marketing knew about what the role actually entailed.

If you fast forward to today, there are so many additional disciplines and components that make up what is (still) referred to simply as ‘marketing’, it’s virtually impossible to expect that a single marketer could possibly master all of them: From creative (copywriting, graphics, web design, animation, podcasts and video production) and SEO, to social media, organic and paid promotion, email marketing, lead generation, conversion optimization, and more. Each of these disciplines has become so sophisticated, there are now entire industries around them, with new technologies and job functions that require specialized expertise to perform them.

In companies with small marketing teams, marketers are usually forced to focus only on their top priorities and be super-efficient with their budgets to achieve their goals. But what’s common to all marketing teams – whether large or small – is the basic premise of marketing, which is promote the company and its products in a way that generates as many new customers and as much revenue as possible.

Marketing exists to create brand awareness and brand loyalty in order to support the brand’s business goals, and all businesses are about boosting revenue (otherwise they wouldn’t be in business).

Given that there are so many moving parts and specializations within marketing teams these days, it makes sense that there’s someone in the team dedicated to optimizing revenue generation efforts. This has given rise to roles like CROs (Chief Revenue Officers), Data Analysts, BI Analysts, Lead-Gen Specialists and others, who sit somewhere between Sales and Marketing, and ensure that the focus of all business activities is firmly set on growing revenue.

But regardless of the job title – the task of understanding customer behavior to maximize the efficiency of marketing strategies so that they meet business goals relies one thing: Data.

For business leaders and marketers who haven’t quite realized it yet, here’s a newsflash: Pretty soon, it won’t be possible to conduct a modern marketing operation successfully without some sort of data expert on the team (yes, the role of the marketer has evolved to require yet another specialization, again).

Pretty soon, it won’t be possible to conduct a modern marketing operation successfully without some sort of data expert on the team.

Why Data Intelligence Is (already) the next big thing in marketing

Consumer data is useless if you don’t know how to leverage it to derive insights that can actually help you in your marketing activities. But once you learn what type of data could help you make smarter decisions about your marketing strategy, and then collect that data and interpret it to create personalized messaging targeted to relevant customers, data starts to become an invaluable tool that can have a meaningful impact on the company’s revenues.

Data has traditionally been collected by various marketing departments as part of their own channel ‘ownership’. For example, email marketers extract their own data through their email marketing software, social media managers gather data from the various platforms they manage, SEO, paid advertising and lead-gen folks collect data using their tools of the trade, and the sales department also has systems to track data pertaining to customer purchases and company revenue. Each department has typically used its own silo of data to create and target marketing and sales initiatives, in what is known as multi-channel marketing, which as the name suggests, means that customers receive similar versions of the same marketing campaigns across several channels.

That was the norm in the 2010s, but the consumer of the 2020s has evolved to expect a more sophisticated level of interaction with brands. To provide it, marketers must use an omnichannel approach, which gives shoppers a unified, hyper-personalized experience across multiple touchpoints in a timely way, based on where they are in the customer journey. This can include brick-and-mortar stores, social media, email, SMS, and any other marketing or sales channels, and the communications they receive are designed specifically for them.

According to a chiefmartec.com and WPP report heralding the Age of the Augmented Marketer, “the 2010s were about big data, wrangling the enormous scale and complexity of data flowing into organizations at an accelerating velocity. The 2020s will be more about “big ops” — the orchestration layer on top of that universe of data and its growing scale and complexity.”

Although the concept of omnichannel marketing has been around for several years, and large retailers have already started using it to great effect, it requires technology that’s still relatively new (and therefore daunting) for most marketers. But in recent years this has begun to change, with CDPs (Customer Data Platforms) becoming more prolific, to meet the growing demand from marketers for automated data collection and analysis.

Accessible, affordable tech is opening up new opportunities for independent retailers because they can now do things themselves that previously were prohibitively expensive, or something only big box stores had the resources to offer.

Kimberly Smith, Founder of Marjani Beauty and Board of Directors member of the National Retail Federation.

What is Data Intelligence, and why marketers of the future need to be data-intelligent.

Sisense define data intelligence as “all the analytical tools and methods companies employ to form a better understanding of the information they collect to improve their services or investments. Today, data intelligence incorporates both artificial intelligence and machine learning tools, which permit organizations to analyze enormous amounts of data much faster and reliably than if done manually.” The technology uses a process called “hashing”, which essentially collects data about individual shoppers without associating them with their actual identities, making CDPs compliant with privacy regulations such as GDPRCCPA and others.

Simply put, data intelligence allows marketers to leverage data in order to make more intelligent decisions about their efforts to increase their customer-base, boost engagement, conversion, revenue and retention.

Reliable customer data can lead to significant insights, where even a relatively small tweak to a marketer’s typical activity or campaign can make a huge difference to conversions. Access to this type of data can therefore be a game-changer for reaching revenue KPIs and take a marketer’s capabilities to a whole other level.

Why data intelligence is a retail marketing ‘superpower’ and why only a CDP can wield it effectively

With a 5,233% increase over the past decade in the adoption of marketing technology tools (also known as MarTech tools) – especially in the past couple of years when retailers increasingly turned to technology for their marketing operation – it’s clear that marketers are embracing digital assistance in the areas of data analytics. And they need all the help they can get, because as we near a post third-party cookie world that puts user-privacy first, marketing strategies will have to be adjusted to leverage other types of data instead, like first-party (data that’s collected passively by brands from their own channels with customer consent) and zero-party data (data that is given voluntarily by users).

First-party data is a treasure trove of information that brands can use to better understand their customers’ preferences and shopping habits, but it is impossible to collect manually at scale. With CDPs and data intelligence platforms that facilitate omnichannel outreach, however, marketers are empowered to create hyper-personalized marketing campaigns, which is why CDP adoption is on the rise, with the global CDP market expected to reach $20.5 billion by 2027.

One of the most notable benefits of CDPs is the aggregation data from all of an organization’s customer touchpoints into a single repository that all company stakeholders can leverage for their various customer communications. With data no longer siloed across different departments and teams, CDPs can keep it from conflicting, becoming redundant, outdated, obsolete or inaccurate. Instead, it provides all team members access to the most real-time, updated customer data available at all times. This makes it a lot easier to achieve a consistent 360-degree customer view of each individual customer, to customize messages and offers that take into consideration many different variables that might influence their shopping decisions.

Another differentiating feature of CDPs, is their ability to automate the organization of vast amounts of data into segments (or, ‘customer cohorts’) based on certain criteria. This allows marketers to make sense of the data and derive actionable insights they can actually use to optimize their campaigns. In the past, if their company also included a BI team (Business Intelligence) or data analysts, they would need to rely on them for this type of data. But with CDPs, it is easily accessible, allowing marketers to create better-targeted campaigns with greater speed and precision.

“Connecting with customers at scale is increasingly about personalization, intelligent automation, and in-moment adaptation based on where the customer is,” says Forrester VP and Principal Analyst, Michele Goetz. “For many organizations, that’s led to the realization that a cloud data and data science platform to build models is only one part of the puzzle. Data and AI need to be at the edge of business in the applications, mobile devices, and machines where customers engage and interact with the business. This is the new world of connected intelligence, and it’s not just for the big tech companies — it’s the required state for any modern enterprise.”

Moreover, data intelligence platforms like Pairzon allow marketers to identify anonymous in-store shoppers by pairing their transactional data with their online identities, enabling retailers to find their in-store audiences online. This is a game-changer for physical retailers, because although a whopping 80% of total retail sales take place in physical stores, most retailers are missing out on valuable data that could help them optimize their digital campaigns for better performance and higher ROI. Platforms like Parizon bridge the offline-online gap for retailers, empowering them to be proactive and precise with their marketing strategies and create highly-targeted, personalized campaigns that enhance the customer experience, boost engagement and brand-loyalty, and increases revenue from a significant portion of customers who might have remained anonymous and unreachable if it weren’t for Pairzon’s technology.

Final thoughts…

The omnichannel mantra of reaching “the right customer with the right message at the right time” has become a guiding principle for marketers in the 2020s due to a shift in how people shop and therefore how brands must adapt to keep up with the new trends. Those that are quick to adopt a data-first mindset will set themselves up for success in the omnichannel age.


Pairzon is an AI-powered, cutting-edge solution that pairs in-store transactional data with customers’ online identities, providing Retail Marketers with unparalleled audience discovery, segmentation, measurement, and purchase intent prediction capabilities.

Get in touch to book a demo and see how Pairzon can help you create and target digital marketing campaigns with maximum precision to improve customer experience, boost ROI and increase revenue.