Competitor Price Monitoring for Electrical Supplies Distributor: PricingCraft Case Study

Learn how PricingCraft helped an electrical supplies distributor automate competitor price monitoring across 20 sites and 2,000 benchmark SKUs, with category-based competitor sets, city-level pricing views, and Excel reports that replaced manual work.

2,000

Benchmark SKUs

20

Competitor Sites

Weekly

Excel Delivery

100%

Pack-Size Normalized

About the client

The company is an electrical supplies distributor with an omnichannel model: dozens of branches, a large B2B project business, and a high-SKU e-commerce catalog. Their catalog spans fast-moving commodity lines (where raw material swings ripple straight into price moves) and specification-driven equipment sold through very different channels.

The problem wasn’t “we need price tracking.” It was more specific and more painful:

  • Pricing was built off baseline vendor price lists and fixed markups that worked fine until the market started moving fast.
  • Competitor behavior wasn’t uniform. The “right” competitors for decorative lighting didn’t look like the “right” competitors for power equipment.
  • Manual monitoring couldn’t keep up, so pricing decisions lagged behind promos and commodity moves. Sometimes they lost traffic because they reacted too late. Other times they left margin on the table by keeping prices unnecessarily low.

They needed a system that made competitive pricing visibility routine and actionable, not a one-off research project.

Electrical Supplies DistributorNDA Protected

An omnichannel distributor operating dozens of branches, a B2B project business, and an e-commerce catalog. Because their specific benchmark SKUs, margin strategies, and city-level pricing rules are highly sensitive, we protect their identity under a strict Non-Disclosure Agreement.

What pre-sales conversations uncovered and what we set out to achieve

In the earliest working sessions, the pricing team described an all-too-familiar loop: someone would pull competitor prices by hand for a narrow set of “indicator” products, compile results in spreadsheets, and then realize the market had already moved again.

The brief

In partnership, we defined goals that tied directly to operational outcomes:
  • Replace manual competitor checks with automated monitoring on a fixed benchmark list (about 2,000 SKUs) so weekly pricing reviews could run on schedule.
  • Segment competitor comparisons by product category so each group was judged against the market that actually influences it.
  • Support commodity-sensitive categories (especially cable) with faster visibility into competitor movement so the team could avoid selling at a loss or missing volume when prices shifted.
  • Capture competitor data in a predefined city-level context so prices and conditions were comparable and usable for local price list decisions.
  • Deliver outputs in the format the team lives in: Excel, with traceable source links and clean normalization rules.

What changed after go-live

  • Monitoring moved from episodic, manual checks to an automated cadence on a benchmark list of about 2,000 SKUs.
  • Competitive data was collected across 20 competitor sites and delivered in Excel, replacing time-consuming manual lookups.
  • Competitor sets were segmented by category so comparisons reflected the market reality for each product group.
  • City-level settings were applied during collection to keep competitor prices and conditions comparable for local decision-making.
  • Packaging differences were normalized using multipliers (for example, converting single-unit competitor prices to match multi-unit packs), so the pricing team could compare like-for-like.
  • The pricing team enhanced their responsiveness to local market shifts, optimizing price positioning and protecting margins based on real-time visibility into regional demand dynamics.

I’ve seen too many monitoring projects fail because the data shows up in a format nobody trusts or can act on. We designed this around the pricing team’s real workflow: clear matching, clear normalization, and reports that make it easy to explain a decision internally.

Elena Stepanova
Elena Stepanova
Elena Stepanova led the engagement and stayed close to the operational details. She brings 5 years in pricing work and 7 years in international marketing, which matters here because the job isn’t “collect data.” The job is “make data usable for decisions.”
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Steps to implement competitor price monitoring for electrical supplies distributor

We treated this as a joint build with the pricing team, because “good data” is only good if it matches how decisions get made.
  • Step 1: Map the competitive landscape

    The first stage of competitor price monitoring for electrical supplies distributor involved mapping 2,000 benchmark SKUs with existing competitor links. That gave us a clean baseline, but it surfaced the next need: category-aware monitoring and regional comparability.

  • Step 2: Set up the collection layer

    We configured data collection protocols to analyze publicly available product listings within specific regional market contexts the team needed. The goal was consistency: the same items, in the same geographic setup, pulled the same way each time.

  • Step 3: Implement matching logic

    We implemented automated matching based on barcodes, then did selective manual checks on sampled matches to confirm the logic held up in the messy corners (pack sizes, near-identical variants, and listing quirks).

  • Step 4: Normalize pricing for packaging

    We added multipliers where necessary. If the distributor sells a 100-unit pack and a competitor sells singles, the system converts the competitor price into the comparable pack-equivalent number.

  • Step 5: Finalizing competitor price monitoring for electrical supplies distributor with custom reporting

    They wanted Excel, not a new dashboard. The report included source links, normalized prices, stock quantity, pack details, and city-level context.

We set the production cadence to weekly collection and delivered the Excel reports via email, so the pricing team could plug the output into their existing review process without changing how they work.

💡 Beyond Custom Excel: The PricingCraft Platform

In this case, the client needed normalized data delivered directly into their existing templates to avoid retraining their team. We fully support this "zero-adoption" approach via automated Excel or API exports.

However, if you don't have an internal pricing dashboard yet, we offer a powerful proprietary platform out-of-the-box. It goes beyond raw data and gives your commercial team a ready-to-use visual toolkit:

  • Built-in Pack & Unit Normalization: Native logic to instantly recalculate and compare competitor prices by weight, volume, or pack size (e.g., singles vs. 100-unit boxes) for true apples-to-apples comparisons.
  • City & Category Segmentation: Slice your competitive landscape by specific product categories or geographic regions to see the real local market dynamics.
  • Smart Price Indexing: Instantly spot where you are overpriced, underpriced, or where competitors are out of stock so you can optimize margins daily.
Explore our price monitoring solution for online retailers

Final results: competitor price monitoring for electrical supplies distributor via Excel

Because the client's catalog and margin strategies are strictly confidential, the example below uses anonymized data. It illustrates the final weekly delivery format: a clean Excel file featuring normalized prices (adjusting for pack sizes like singles vs. 100-unit boxes), stock availability, and traceable source links.

Weekly competitor price monitoring report for electrical supplies, delivered via automated Excel export with pack-size normalization.

When technical accessibility for scraping becomes complex, reliability becomes the product

The hardest part wasn’t the spreadsheet. It was ensuring consistent data accessibility from diverse market sources, regardless of their technical infrastructure complexity

The challenge
Key market players utilize complex technical infrastructures that require sophisticated data interaction protocols to maintain accuracy. That can turn a pricing program into a whack-a-mole exercise where analysts spend more time troubleshooting than analyzing.

Resolution: Resilient collection patterns

How we addressed it
PricingCraft’s scraping infrastructure is designed for data integrity: proactively adapting to the natural evolution of digital market sources. Our infrastructure utilizes industry-standard request optimization to ensure data accuracy while respecting target server stability. The practical outcome for the client was simple: the pricing team didn’t burn cycles on access issues, and the data flow stayed consistent enough to support a predictable review cadence.

Resolution: Proactive infrastructure monitoring

Two practical lessons for electrical distribution price monitoring

Lesson 01

Weekly beats “perfect” in volatile categories

In commodity-sensitive lines, value comes from a steady cadence you can rely on. A weekly report lets the team run the same playbook: spot outliers, confirm what changed, and decide where to move. Consistency turns monitoring into an operational habit.

Lesson 02

Normalization is where credibility lives

Pricing teams lose trust fast when pack sizes, unit counts, or availability aren’t handled cleanly. Once you standardize comparisons and keep source links in the report, arguments shift from “is the data wrong?” to “what decision are we making?”

Ready to launch competitor price monitoring for electrical supplies distributor and turn it into a repeatable pricing routine?

If your pricing team is still stitching together competitor checks by hand, the biggest cost isn’t the time. It’s the decisions you don’t make fast enough, and the margin you quietly give away where the market would support more.

PricingCraft works best as a long-term partner: an expert team that can run a dependable monitoring program through the messy reality of modern e-commerce sources, while keeping outputs tied to business decisions. Whether you start with the SaaS platform or a custom data extraction build like this one, the goal is the same: pricing visibility you can use every week.

Next step:

Request a demo or ask for a pilot. We’ll map your benchmark list, define category competitor sets, and show you exactly what your weekly Excel report could look like before you commit.

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