Numerator is a powerful DIY research tool that offers detailed insights into shopper behavior. But when it comes to analyzing brand portfolio fit, teams often hit a wall. It’s not that the data isn’t available – it’s that interpreting it correctly takes experience, strategic framing, and a nuanced understanding of categories, brands, and consumer behavior.

Here are some of the most common problems teams face when using Numerator for brand portfolio analysis:

1. Difficulty Framing the Right Research Question

Before you even start analyzing data, there’s a need for clarity around the business question. Teams often dive into Numerator hoping to see buyer crossover between brands or products, but forget to define what “portfolio fit” actually means in their category. Without a tight, objective-aligned question, the output can miss the mark – or worse, lead to false conclusions.

2. Lack of Consistent Category Architecture

Numerator enables flexible filtering and cross-tab options, but that flexibility comes at a cost. If your team hasn’t aligned on a consistent definition of SKUs, brands, or usage occasions, comparisons will be inaccurate. For example, treating protein bars and granola bars as part of the same portfolio may work for one company but lead to misleading insights for another.

3. Challenges Identifying Meaningful Overlap

When analyzing SKU overlap, Numerator will show which buyers purchase across products – but that’s only the surface. It doesn’t tell you why a shopper moved between SKUs or whether the change was intentional, habitual, or promotional. Connecting these dots requires human insight, especially if you’re considering innovation or repositioning.

4. Misinterpretation of Low-Incidence Behavior

In brand stretch analysis, small buyer groups can produce outsized influence if not correctly weighted. Just because 5% of buyers cross between two unrelated product SKUs doesn’t mean those categories make strategic sense together. Without expert interpretation, teams may chase low-value signals or overlook more promising opportunities.

5. Gaps in Internal Expertise

Many insights teams are lean, especially today. While they may have access to tools like Numerator, they may lack a category strategist who can translate raw data into brand or product recommendations. This creates a growing reliance on external expertise to validate findings and pressure-test assumptions.

Ultimately, Numerator excels at giving you data – but to turn that data into smart brand decisions, you need guidance. That’s where On Demand Talent comes in, giving companies access to experienced professionals who know how to frame, filter, and interpret for maximum impact.

On the surface, analyzing SKU overlap and brand stretch in consumer insights tools like Numerator sounds straightforward. After all, you're simply looking to see if the same shoppers buy more than one product across your portfolio. But the reality is more nuanced – and more prone to missteps if you’re not cautious.

Here’s why identifying brand stretch opportunities or portfolio gaps in Numerator data requires more than just a basic analysis:

Category Blending Can Obscure True Fit

In some categories, especially those with fast-moving SKUs or blurred benefits (like beverages or snacks), consumers may frequently switch between options. This doesn’t necessarily signal strong portfolio synergy. For instance, a shopper buying sports drinks and flavored waters might be behaving out of convenience rather than loyalty. Without understanding category norms or shopper motivations, overlap can easily be misread as brand stretch potential.

Brand Stretch Isn’t Just About Purchase Behavior

A true brand stretch opportunity means your brand has earned the right to play in a new space. Seeing overlap between toothpaste and mouthwash doesn’t mean consumers want your brand in both categories. That depends on perceptions, trust, and relevance – something Numerator data alone can’t measure. This is where pairing behavioral data with expert brand interpretation is critical.

SKU Overlap Can Be Statistically Misleading

One of the most common insights software issues occurs when overlapping purchase behavior is over-weighted or reported without statistical rigor. A small sample might look like a trend, especially if slice-and-dice filters are applied inconsistently. Skilled researchers understand how to validate whether overlap is truly significant or just noise in the data.

• False Positives: Customers who buy two products during a promotion may indicate overlap, but that behavior may not be sustained.
• Underreported Fit: Meaningful connections may go unnoticed if filters are too broad or categories aren’t defined clearly.

Internal Teams May Miss the Bigger Picture

Most marketing or research teams are focused on specific brands or verticals, which can create blind spots. Forcing the data to answer a narrow question – like "Do buyers of our almond milk also buy our plant-based yogurt?" – without context can lead to misguided brand extension ideas. A broader, category-informed view is key to spotting the right stretch plays.

Expert Help Makes the Difference

If you've ever wondered why your Numerator tool is not showing SKU connections or how to analyze brand stretch in Numerator effectively, you're not alone. The truth is, tools like Numerator are only as good as the people interpreting them. SIVO’s On Demand Talent professionals come with deep category expertise and real-world experience in framing the right research approaches, ensuring that your insights remain both strategic and actionable.

With increasing reliance on DIY research tools, the need for human expertise hasn’t disappeared – it’s become more essential. By partnering with experienced insights professionals, brands can enhance their use of software tools and build long-term capability within the team.

Numerator provides a robust way to explore what consumers buy and how they interact across product lines – but raw data alone doesn’t always tell the full story. Even with easy-to-use dashboards, category-specific expertise remains essential for uncovering the 'why' behind the data. This becomes especially important when tackling complex questions around brand stretch, SKU overlap, or portfolio fit.

Let’s say you're a beverage brand trying to understand if sparkling water buyers are also purchasing flavored sodas in your brand lineup. Numerator might show some cross-shopping, but surface-level analysis doesn’t explain the behavior. Are they loyal to your brand? Are they switching based on promotions? Or are your brand variants positioned too similarly? That’s where category knowledge comes in.

Why Deep Category Expertise Makes a Difference

• It helps decode subtle shopper behavior patterns that aren't obvious from numerical data alone.
• Category experts bring a contextual understanding of pricing tiers, distribution strategies, and consumer purchase drivers.
• They can spot biases or blind spots in how the Numerator tool is being used – for example, default filters that mask pivotal overlaps.

Without this lens, it’s easy to make decisions on incomplete interpretations. Internal teams may mislabel occasional cross-buying as brand stretch, or misjudge portfolio gaps due to technical setup errors within the software.

Expert interpretation ensures you're not just measuring SKU overlap – you're understanding what it means. This is especially valuable in highly competitive categories with complex segmentations, like personal care or snacks, where small shifts in buying behavior can have outsized strategic impact.

By pairing Numerator outputs with category-savvy professionals, your team can uncover smarter, more nuanced insights – and avoid one-size-fits-all conclusions.

With more companies adopting DIY research tools like Numerator, there’s a growing need for in-house teams to do more with less. But while these platforms offer powerful analytics, they can fall short when teams lack the hands-on expertise to navigate complex features, interpret the outputs, or adjust strategies when results are unclear.

This is where SIVO’s On Demand Talent comes in. These professionals step in quickly to help insights teams bridge the gap between expectations and execution – whether you’re launching a brand fit study or investigating SKU performance across your full portfolio.

Solving Common DIY Research Tool Challenges

Many teams get tripped up by:

• Misinterpreting buyer behavior due to default dashboard settings
• Overlooking important SKU connections because filters are improperly applied
• Lacking the category expertise to distinguish between meaningful brand stretch and coincidental cross-purchasing
• Needing to train internal staff while keeping projects moving

SIVO’s On Demand Talent professionals address these problems by providing hands-on help while also mentoring your team along the way. This creates a double benefit: improving the accuracy of current work while strengthening internal capabilities for future studies.

Unlike traditional freelancers, our On Demand Talent are seasoned consumer insights experts. They’re embedded into your existing team structure and add strategic guidance without requiring long onboarding ramps. Their job isn’t just to run reports – it’s to help your team make confident, informed decisions and get the most out of platforms like Numerator with minimal disruption and maximum ROI.

Whether you need help analyzing brand stretch in Numerator or troubleshooting issues with SKU overlap visibility, our experts can jump in fast, provide clarity, and put your insights team back on a strategic track.

Numerator is a powerful investment for any insights-driven organization – but like any analytics tool, its power depends on how it’s used. Without experienced interpretation and proper setup, even the most data-rich dashboards can lead to missteps, such as assuming brand stretch where none exists or misreading category opportunities. To truly maximize Numerator's potential, organizations need more than access – they need expertise.

If you’ve ever run into challenges like unclear SKU overlap results, redundant buyer tracking, or confusion interpreting multi-brand relationships, you’re not alone. These are common issues when DIY tools are used without strategic support. The good news? You don’t have to go it alone.

How Expert Support Transforms ROI

SIVO’s On Demand Talent professionals bring the skills and experience needed to make Numerator work harder for your team. By embedding our experts into your insights workflow, we help you:

• Diagnose and correct flawed configurations that may be skewing results
• Reveal hidden connections between brands or SKUs that impact how you design your portfolio
• Ensure research aligns with strategic decisions, not just tactical reporting
• Hand over best practices that upskill your internal team for long-term independence

Imagine using Numerator not just as a way to report on what’s happening – but as a strategic compass that guides portfolio growth, identifies category whitespace, and supports brand expansion decisions. That’s where SIVO’s experts deliver lasting value.

Because our talent works on-demand, you don’t need to hire full-time or wait months to get help. We can plug in when you need added horsepower – whether for a short-term assignment, a quick-turn data deep dive, or a longer engagement to build up internal knowledge and confidence in the platform.

In today’s world where DIY tools are everywhere but insights teams are stretched thin, tapping into expert help is a smart move. With SIVO, you protect your research investments and ensure every decision powered by Numerator is grounded in real insight and expertise.