What does ClearDemand need from our IT team?

A data spec conversation, a file drop, and access to your POS and ERP. ClearDemand configures to your data model rather than asking you to reshape data to ours, and runs project management from our side through go-live. The realistic ask is scoped hours, not a dedicated resource. FMI found food retailers roughly doubled technology spend to about 2% of sales in 2026, so the constraint is rarely budget. It is your team's capacity.

How does competitive data get collected and matched?

Patented collection across competitor websites, apps, and APIs, with anti-bot handling, anomaly detection, continuous quality audits, and crawler maintenance behind the scenes. Machine-learning matching is built for grocery, so fresh, produce, deli, bakery, and meat are handled with pack sizes and units equalized across national brand, private label, and organic. Accuracy runs at 90% exact or equivalent, and your team verifies flagged matches in a prioritized queue.

What integrations already exist?

Live connections to NCR HQ, PDI, SAP HANA, and Oracle NetSuite, with a 240+ retailer collection network on the competitive side. Adding a competitor to your set is our work, not a new integration on your backlog.

How do we get priced output back into our systems?

SFTP, S3, Snowflake, or BigQuery, and downstream to stores, shelf labels, and replenishment. To be direct about a gap: there is no customer-facing outbound pull API today. BigQuery pull from a customer-provided table is the modern path, and a pull API is on the roadmap.

What is your security and compliance posture?

SOC 2, single sign-on, and role-based access control. Documentation and SLA terms are available during evaluation rather than after signature, and we would rather you define the SLA parameters than have us impose them. Gartner found 91% of retail IT leaders rank AI as their top 2026 priority, which puts governance of AI decisions on your desk. Every recommendation, override, and outcome is logged with its inputs and human checkpoints.

How long does implementation take, realistically?

Competitive intelligence typically delivers first value in 30 days, ahead of full optimization rollout. NVIDIA's 2026 retail research found 91% of retailers are using or assessing AI while only 20% run agents in production, and the bottleneck is data plumbing, governance, and integration rather than the model. That is exactly the work ClearDemand takes on, and we would rather match your roadmap than push a date you cannot hold.

What happens when a competitor site changes or a match breaks?

Crawler maintenance and re-matching are handled on our side. Matches re-form automatically when products change or disappear, anomaly detection sits between the competitive feed and the optimization engine, and quality audits run continuously. When something does break, it is our incident to resolve, and one customer measured a failed overnight job caught and fixed in fifteen minutes.

Should we just build this ourselves?

Plenty of teams try. A model trained on your own transaction history predicts your own past and carries no competitive signal at all. The collection side is harder: anti-bot handling across 240 retailers, matching that survives pack size and private label, and crawler maintenance that never ends. One regional grocery chain spent hundreds of thousands migrating an in-house competitive pricing app, then looked at consolidating it away. The question is whether you want your team maintaining it for the next decade.

ClearDemand for IT

One unified platform for competitive data, pricing, and promotion.

ClearDemand scrapes competitive price data, optimizes price and promotion on your POS and cost data, and delivers priced output back to your systems. We configure to your ecosystem and run the project.

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10x

faster data cleansing

40%

lower data management cost

30 days

to first comp intel value

Retail data is disparate and messy. Cleaning it should not take all week.

Competitive data comes from one vendor, pricing from another, promotion from a third, and reconciling them is nobody's job until something breaks. ClearDemand runs competitive intelligence, price optimization, and promotion on one platform built for grocery and convenience, so there is one connection to build and one to maintain.

Three systems to connect

Competitor scrapes break and someone rebuilds

Match failures surface as wrong prices

Every new competitor is a new integration

Cost feed gaps get found downstream

Anti-bot defenses change without notice

Pack size and private label defeat matching

Pipeline knowledge lives with one engineer

Every vendor wants a different file format

One unified data platform

Crawler maintenance handled behind the scenes

90% exact or equivalent match accuracy

240+ retailers on one collection network

Anomaly detection before data reaches you

Continuous quality audits on the feed

Pack size and units equalized automatically

We configure to your data model

We deliver to SFTP, Snowflake, or BigQuery

Talk to our engineers

Built so your backlog does not grow

Retail IT is already running POS, ERP, loyalty, and analytics with a team that is fully committed. A pricing platform should reduce that load rather than add to it.

90% exact or equivalent match accuracy

Machine-learning product matching across 240 retailers and 7M data points built for grocery: fresh, produce, deli, bakery, and meat, with pack sizes and units equalized across national brand, private label, and organic.

Explore Competitive Intelligence

Security and access, documented before you ask

SOC 2, single sign-on, and role-based access come standard, with documentation and SLA terms available during evaluation rather than after signature.

Explore the Platform

What building this yourself actually costs

Twelve to 18 months to a model that predicts your own past, with no competitive signal in it. Then the collection side: anti-bot handling across 240 retailers, matching, and maintenance that never ends.

Read build versus buy

What has this looked like for other IT teams?

Data costs down 40%, insight generation up 200%

A grocery retailer automated its competitive data feed and product matching, cutting what it spent managing that data and freeing the team for strategy.

Read the full case study

40%

lower data cost

10x

faster cleansing

200%

more insight

One collection network, 240+ retailers, 7M+ records a day

The competitive data pipeline runs on ClearDemand infrastructure, with anti-bot handling, anomaly detection, and crawler maintenance behind the scenes.

Read the full case study

7M+

records daily

240+

retailers tracked

30 days

to first value

A failed overnight job, caught and fixed before anyone noticed

The analyst lead at a large regional grocer saw the failure notice and the fix notice at the same time. Fifteen minutes, and the number came from the customer unprompted.

15 min

from failure to fix

"We have used ClearDemand as our only trusted competitive intelligence platform to price our products competitively 24/7 and increase our selection year over year."

Retail data team

ClearDemand customer

INTEGRATIONS

What does implementation require from us?

A data spec, a file drop, and access to your POS and ERP. ClearDemand configures to your data model rather than the reverse, runs project management from our side, and NCR HQ, PDI, SAP HANA, and Oracle NetSuite are already connected.