Introduction
Stocking the right assortment of products based on diverse factors such as customer preferences, geographical location, season (among others) plays a crucial role in selling products effectively.
An even more crucial factor is dynamically updating the assortment mix using a data driven approach. Specifically, data that throws light on products that are missing from catalog, but that are present in a competitor’s or in the supplier’s catalog. Identifying and fixing Assortment Gaps can make a great difference to revenues.
What causes assortment gaps?
Assortment gaps in distributors' catalogs stem from several strategic and operational blind spots:
- Geographic Mismatches
- Distributors fail to tailor assortments to local demand (e.g., climate-specific products like swimwear in warm regions) or replicate inventory inconsistently across postal codes.
- Insufficient Competitive Intelligence
- Missing competitor best-sellers (e.g., only 5 snack flavors vs. a rival’s 15) or ignoring key product attributes (e.g., omitting 32GB RAM laptops when competitors offer them).
- Poor Assortment Planning
- Depth vs. width imbalances: Overly broad catalogs with shallow brand options (e.g., 1–2 pet food brands) or excessive depth in one category (e.g., 50+ shoe variants) causing gaps elsewhere (such as compatible insoles).
- Incomplete Product Variants
- Skipping key sizes/formats (e.g., no single-serve beverages for convenience stores) or inconsistent packaging data (e.g., listing "12oz packs" online but "350g boxes" in-store).
- Lack of Market Trend Tracking
- Failing to add emerging categories (e.g., gluten-free foods, eco-friendly packaging) due to outdated demand forecasts.
What is the impact of assortment gaps?
Apart from the obvious impact on revenues, these gaps impact other areas such as customer experience and operations. Here’s a breakdown:
1. Financial Losses
- Direct revenue leakage: Gaps in high-demand categories (e.g., missing 32GB RAM laptops) can reduce category sales by 15–30%
- Profit erosion: Substitute purchases (e.g., buying from competitors) cost distributors 2–5x more in lost lifetime value versus retaining the customer.
- Carrying cost inflation: Overstocking unrelated SKUs (e.g., 50+ shoe variants) to "compensate" for gaps can increase dead stock by up to 18%.
2. Customer Experience Erosion
- Cart abandonment: Online B2B buyers abandon purchases 28% faster when core products (e.g., industrial solvents) are missing.
- Brand distrust: Inconsistent availability (e.g., cereal listed as "12oz online" but "350g in-store") confuses buyers, reducing repeat purchases by 22%.
- Channel cannibalization: Shoppers forced to visit 2+ stores/websites to complete orders show 40% lower loyalty scores.
3. Market Share Decline
- Competitor leverage: Gaps in trending categories (e.g., eco-friendly packaging) allow rivals to capture >50% of emerging demand within 6 months.
How can you keep up with these gaps?
Identifying assortment gaps is like finding a needle in a haystack — inefficient, error-prone, and costly. Key hurdles include:
1. Data Overload & Fragmentation
- Multi-source chaos: Analysts must reconcile siloed data from ERP, POS, competitor catalogs, and supplier portals, often in incompatible formats (e.g., Excel, PDFs, web scrapes).
- Volume overwhelm: A mid-sized distributor tracks ~50,000 SKUs; manually comparing these against 10+ competitors’ catalogs (500K+ data points) is physically impossible.
2. Time Lag & Stale Insights
- Weeks-long processes: Manual audits take 3–6 weeks to complete — by which time competitor assortments, demand trends, or inventory levels have already shifted.
- Real-time blind spots: Example: A hardware distributor’s team spent April manually verifying SKUs, missing a competitor’s May launch of eco-friendly paints (capturing 17% market share by June).
3. Human Error & Bias
- Inconsistent attribute mapping: One analyst labels "vegan shampoo" as hair care, another as ethical products, creating false gaps or overlaps.
- Confirmation bias: Teams prioritize "known" categories (e.g., top 20% SKUs by revenue), ignoring emerging niches (e.g., pet CBD products).
4. Geographic & Channel Complexity
- Localized gaps invisible at HQ: Store-level assortments in rural vs. urban branches vary widely; manual checks rarely sample beyond "flagship" locations.
- E-commerce vs. in-store blind spots: Online catalogs update hourly, while physical store audits happen quarterly — making omnichannel gap detection unreliable.
5. Hidden Costs & Burnout
- Resource drain: Teams waste 60–70% of time on data collection vs. analysis. Example: Sales reps lose 20+ hours/month compiling gap reports instead of selling.
- Talent attrition: Skilled analysts quit due to repetitive tasks; turnover rates in retail planning roles exceed 25% (2024 Retail HR Report).
6. Strategic Limitations
- No root-cause analysis: Manual methods identify what’s missing but rarely explain why (e.g., gaps due to pricing? packaging? demographic shifts?).
- Inability to simulate scenarios: Teams can’t manually model how adding 10 new SKUs impacts inventory costs or cannibalization rates.
Additionally, manual processes do not scale—it typically takes 10 times the number of human resources to scale 2X! Error rates are up by 35% in attribute matching, and customer trends are often missed.
So what are you waiting for? Adopt automation today!
