Today’s retail landscape is anything but linear. Shoppers are no longer loyal to a single channel – instead, they mix and match as they see fit. A typical path might include comparing prices online, purchasing in-store, and subscribing to an auto-ship option through a retailer's app. While this flexibility benefits consumers, it creates added complexity for brands trying to track and analyze these journeys.

Understanding how consumers shop across multiple channels – also called omni-channel or multi-channel behavior – is critical for effective decision-making. It informs everything from product placement to promotional strategy to channel investment. But decoding this behavior is no easy task. Here’s why:

1. Shopping Journeys Are Non-Linear and Personalized

Consumers take unique paths to purchase. Two shoppers may buy the same product but through different channels, at different times, and for very different reasons. This makes it hard to generalize patterns or segment shoppers without a comprehensive view of their behaviors.

2. Channels Report and Track Data Differently

Mass, club, ecommerce, and convenience channels often measure data in their own formats, creating inconsistencies that make it hard to align insights. For example, purchase timing or basket size might be reported differently across channels, making apples-to-apples comparisons difficult.

3. Context Is Often Missing in DIY Research Tools

Numerator does a great job of capturing transactional data, but interpreting the ‘why’ behind behaviors– like why a shopper chose online over in-store – typically requires additional expertise or layering in qualitative insights. Without this context, teams risk misreading signals or acting on assumptions.

4. Micro-Trends Are Easy to Miss

Small behavioral shifts in a single channel can have big implications, especially in ecommerce. If you're only looking at total sales or top-line trends, it's easy to miss nuance like channel switching, trial behaviors, or bundling preferences.

Altogether, analyzing cross-channel shopping behavior requires both a tool like Numerator and the expertise to interpret the data in a strategic, actionable way. As brands grow more reliant on faster, more agile research, closing these interpretation gaps becomes essential to keeping pace with today’s shoppers.

Numerator is an increasingly popular DIY research platform for tracking shopper behavior across multiple retail channels. Its strength lies in capturing rich, transaction-level data across mass, club, ecommerce, and convenience retailers. But while the platform offers robust capabilities, many teams face persistent challenges when using it for multi-channel retail analysis.

Here are some of the most common issues that can arise – and what to keep in mind if you’re struggling to turn raw data into meaningful insights:

Lack of Context in Shopping Journeys

Numerator provides the ‘what’ – what was purchased, where, and when. But it doesn’t always tell you the ‘why.’ For example, a sudden increase in online purchases might seem like a trend, but there could be multiple reasons behind it: promotions, availability, convenience, or even stockouts in physical stores. Without context, the data can be easy to misinterpret.

Inconsistent Channel Comparisons

Each retail channel operates differently. Club stores, for instance, often feature larger pack sizes or subscription-style purchasing that skews purchase frequency data. Ecommerce trends, on the other hand, may reflect promotional events, shipping delays, or mobile commerce habits. If you're analyzing all channels the same way inside Numerator, you may miss key nuances.

Difficulty Visualizing Cross-Channel Behavior

One of the most valuable insights is understanding how consumers transition between channels – say, browsing online before buying in-store, or trying a product in-store before reordering it through a subscription service. Visualizing these cross-channel purchase patterns within Numerator requires skill and time. Many teams don’t have easy ways to map these journeys cohesively.

Overwhelmed Internal Resources

As Numerator and other DIY research tools grow more sophisticated, they also place more demands on insights teams. It’s no longer just about pulling data – it’s about interpreting it, storytelling with it, and tying insights to larger business goals. But with lean budgets and team bandwidth at a premium, these tasks often fall by the wayside.

Skill Gaps in DIY Research Tools

Even experienced researchers may not know how to make the most of the technical features within Numerator. From using advanced filters to segmenting by shopper types or visualizing ecommerce vs. physical purchase overlap – these tasks require expertise that isn’t always available in-house.

• Example: A brand team may pull multi-channel data but struggle to identify which channel is driving trial vs. repeat purchases. Without clarity, briefing marketing or sales becomes difficult and decisions stall out.

That’s where On Demand Talent can have a game-changing impact.

By bringing in experienced insights professionals – even temporarily – brands can close skill gaps, get more value from their Numerator subscription, and avoid spinning their wheels. These experts know how to analyze shopping journeys in Numerator, spot inconsistencies, and offer guidance that goes beyond just pulling charts. More than a plug-and-play resource, On Demand Talent builds internal capabilities so teams can run smarter, faster, and more confidently across all retail channels.

DIY research platforms like Numerator are powerful tools for tracking and analyzing shopping journeys. They offer quick access to high volumes of multi-channel retail data and allow brands to explore ecommerce trends, retail channels, and shopper behavior on their own terms. However, relying solely on DIY research tools also comes with some serious limitations – particularly when trying to interpret the full consumer story across mass, club, ecommerce, and convenience.

The challenge isn’t that Numerator lacks feature depth. Instead, teams run into problems when the tools are used without the right context, expertise, or methodology. Multi-channel analysis often requires more than just pulling data – it involves asking the right questions, understanding shopper motivations, and connecting the dots between fragmented data points. When used in isolation or by less experienced users, even the most robust DIY platforms can fall short.

Common gaps DIY tools can’t easily fill

• Lack of contextual understanding: The data shows what’s happening, but not always why. Tools alone don’t reveal the motivations behind switching between ecommerce and brick-and-mortar or why a shopper prefers club retailers for specific occasions.
• Limited ability to compare across channels: DIY interfaces often display channel data side by side, but lack features to truly visualize and compare cross-channel purchase patterns in a meaningful way.
• Difficulty uncovering deeper insights: DIY users sometimes stop at surface-level patterns because they don’t know how to dig deeper, apply frameworks, or use strategic lenses to find actionable results.

For instance, a fictional snack brand might notice in Numerator that 30% of its ecommerce buyers also shop in club channels, but without expert interpretation, they might miss the insight that those shoppers favor different pack sizes or undergo entirely different purchase drivers depending on the channel.

Letting DIY tools guide your entire research journey may cause brands to miss the larger picture – especially when synthesizing multi-channel shopper behavior. That’s where the human element becomes essential. Data is the foundation, but expert analysis transforms that data into clear, accurate, and strategic insights.

To unlock the full potential of platforms like Numerator, many brands are turning to flexible support models like SIVO’s On Demand Talent. These seasoned consumer insights professionals bring the expertise needed to turn multi-channel data into meaningful stories that support better decisions – without the cost, delay, or commitment of full-time hires.

Numerator offers a wealth of raw data on shopper behavior, but pulling out the “so what?” takes a different skillset. On Demand Talent can partner with your internal teams to overcome barriers in DIY research tools and help you:

Translate data into strategic insights

On Demand professionals use established frameworks to interpret how shoppers move between ecommerce, club, mass, and other channels. They help teams go beyond dashboards – connecting data points to form holistic views of shopping journeys that inform marketing, product, and retail strategies.

Fill skills or staffing gaps quickly

Whether your team is newly adopting a DIY tool or simply short-staffed, On Demand Talent can step in as skilled partners. From navigating complex Numerator interfaces to refining hypotheses, they bring experience that enables faster ramp-up and higher-quality outputs.

Customize approaches across your business

Not every business uses Numerator the same way. On Demand professionals tailor their support to your category, business needs, and research objectives – whether that’s visualizing ecommerce and in-store shopping overlap, uncovering friction in multi-channel buyer paths, or optimizing promotions by channel preference.

For example, a fictional emerging beverage brand used On Demand Talent to segment its multi-channel buyers and identify distinct shopping missions by channel. The result? Smarter packaging decisions and targeted retail strategies that better aligned with actual purchase behaviors.

By combining the efficiency of DIY tools with the flexibility and expertise of On Demand Talent, teams can increase the ROI of their research investments and finally bridge the gap between raw data and business-ready recommendations.

Knowing when to seek expert support can make the difference between simply using Numerator and truly gaining insights from it. While DIY platforms empower teams to work faster and more independently, there are clear signals that additional support could elevate outcomes – or save your team from spinning its wheels.

Key signs it’s time to bring in expert help

• Uncertain how to approach analysis: If your team is unsure where to begin or feels overwhelmed by the volume of data, expert help can provide structure and momentum.
• Insights aren’t translating into action: You may be pulling reports or creating nice visuals, but stakeholders aren't using the insights to guide decisions – often a sign the story or strategy isn’t clear enough.
• Struggling to compare retail channels: Analyzing overlapping buying behavior across ecommerce, club, and mass retailers can be complex. If insights feel fragmented, that’s a red flag.
• Your team lacks time or specialized skills: Even experienced insights professionals can be stretched too thin or lack deep expertise in multi-channel analytics or DIY platform navigation.

If these challenges sound familiar, it may be the right time to explore On Demand Talent. Unlike freelancers or agencies who come in with rigid scopes, SIVO’s On Demand professionals integrate seamlessly with your team on your terms – whether it's to support a strategic priority, tackle a temporary surge in workload, or level-up your team's data interpretation skills.

Think of them as an extension of your team that helps you build capability while delivering value right away. For startups looking to punch above their weight, or enterprise teams managing across multiple tools and datasets, this flexible model ensures that insight generation doesn’t slow down when internal capacity does.

Ultimately, your data tools are only as powerful as the people using them. Bringing in expert support – even for a short time – can uncover insights that move the business forward and help your team grow stronger in the process.