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Gradient MSP StackTracker Puts AI Focus on Business Decisions

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Most companies that serve MSPs today are embedding generative AI and automations into their platforms to make operational technology better for MSPs -- improve workflows, speed up service desk ticket closures, and generally make operations more efficient.

But AI has the potential to do much more than that for MSPs. What if you could point AI at all the data collected by your many tools and platforms and then ask AI for recommendations about how to improve your business operations, too?

For instance, how many of your customers are using all the technologies in your stack? Can you generate a list of customers not using a particular service and target those customers for the upsell?

Which of your vendors have proven the most profitable for your business? What is the most profitable vendor to consolidate your clients onto for, say, BDR?

Those are the kinds of questions that Gradient MSP is seeking to answer for MSPs with StackTracker, a SaaS product designed to redefine the way MSPs track their business and make strategic, data-driven decisions.

StackTracker's AI: What it Does, How it Helps

StackTracker provides insights into product category coverage, vendor spend, resale revenue, and profitability on both product and client levels.

“It’s not looking at some representation of what MSPs think they’re supposed to be billing or what they are set up to bill. We are able to capture and understand what their cost is for those solutions,” said Colin Knox, founder and CEO. “Now we can quantify what the value in profit is to MSPs to consolidate to one vendor in a category. They know what their volume is, they know what their margin is, they know who their best margin provider is.”

The software is designed to help MSPs make better business decisions and determine how they will sell into customers.

It’s a natural outgrowth for Gradient MSP, which began in 2020 working to improve the data hygiene of PSA platforms for MSPs later followed with a billing solution. Data hygiene is not the sexy topic that’s talked about with the same fervor that seems to be reserved for generative AI. But data hygiene and data quality are core to generating quality insights from AI. Garbage in, garbage out. By focusing on data hygiene at the beginning, Gradient MSP has set the table for this bigger AI play that is unlike the generative AI approach offered by other MSP platform vendors.

It might be described by some as predictive analytics. It’s making recommendations to MSPs about how to better operate their businesses based on the data from the businesses.

What’s in the Box: StackTracker

StackTracker introduces automated product usage tracking and near real-time data updates, complemented by comprehensive revenue, cost, and profit analytics. Its integration catalogue combined with flexible data grouping, sorting, and filtering, plus AI- driven data analysis with performance trending offer unmatched business insights.

It offers 60-plus native integrations with the most popular PSA, RMM, backup, and cybersecurity vendors. The company said StackTracker is tailored for MSPs to power their growth with advanced reporting and intelligent recommendations for business improvement.

StackTracker’s near real-time visibility into tech stack consumption and utilization can empower MSPs to capitalize on IT spend by identifying opportunities within their client base to drive profitable growth, the company said.

StackTracker is available to a small cohort of 100 MSPs to start, and then a waitlist of MSPs. Knox said the company plans to work in cohorts of 100 MSPs going forward for now.

Gradient MSP StackTracker Puts AI Focus on Business Decisions

Gradient MSP is building on previous work to apply AI to MSP data to help improve profitability.

Jessica C. Davis

Jessica C. Davis is editorial director of CyberRisk Alliance’s channel brands, MSSP Alert, MSSP Alert Live, and ChannelE2E. She has spent a career as a journalist and editor covering the intersection of business and technology including chips, software, the cloud, AI, and cybersecurity. She previously served as editor in chief of Channel Insider and later of MSP Mentor where she was one of the original editors running the MSP 501.