At a retail company described in one of Decision Foundry’s case studies, the obstacle to a new analytics system was a familiar grid. Employees knew Excel. They trusted its rows, columns, and predictable routines. Tableau offered more possibilities, but those possibilities arrived wearing an unfamiliar face. The consultants’ first move was wonderfully unglamorous: make the new dashboards look like the old tables.
- Connect scattered data so teams can work from consistent numbers.
- Make Salesforce and analytics tools fit the daily workflow.
- Add AI with clear controls and measurable results.
The spreadsheet was a clue
The retailer’s rollout began with recognizable views and introduced visual exploration alongside them. Decision Foundry reports more than 90% active weekly Tableau usage within six months. The important detail is the sequence. Familiarity gave people a reason to enter; useful new capabilities gave them a reason to stay. The lesson for anyone commissioning a dashboard is practical: preserve the part of the old routine that helps people think.
A new name for an old problem
Decision Foundry officially launched its identity in April 2022, focused on Salesforce Marketing Cloud, Datorama, and Tableau implementations. Its launch announcement described a business adjusting to growing customer demand. Then-CEO Ross Jenkins said it needed to “develop and grow our Salesforce delivery services.” This was a change in focus and identity for an existing practice, rather than evidence that its entire experience began that April.
Today, the firm works across data engineering, analytics, Salesforce consulting, and AI applications. It sits between the companies selling enterprise platforms and the organizations trying to make those platforms useful. Buyers include agencies and enterprise marketing, sales, analytics, and operations teams. The recurring problem is that buying capable software leaves plenty of work behind: connecting systems, agreeing definitions, changing processes, and getting people to participate.
The connections are the work
Consider its published digital-bank case. Marketing performance was scattered across email, SMS, and push. Analysts joined CSV files manually, and the reporting environment struggled beyond roughly two million rows. Decision Foundry connected Salesforce Marketing Cloud data to Marketing Cloud Intelligence, standardized the relationships and timestamps, and automated the reporting pipeline.
The company reports refresh times falling from more than 24 hours to under two hours, with over 20 million records supported. Those are vendor-reported results from an unnamed customer. Still, they identify a concrete intervention: replace repeated manual reconciliation with a shared data model and automated refresh. The useful question for a buyer is how much of their own reporting delay comes from the same work.
PepsiCo is a named example. Decision Foundry describes building a custom Insights Engine inside Datorama, combining franchise- and brand-level media data with augmented insights and a machine-learning response model. That assignment makes its role easier to understand: the client already has data and technology; the consultancy builds the connections and interpretation needed to answer the client’s particular questions.
Three products, three points of friction
Some repeated problems have become products. CampTag governs campaign names and tracking parameters. Different teams can otherwise give the same campaign incompatible labels, leaving analysts to repair the differences later. Workspaces, validation rules, and bulk creation move some of that discipline upstream, to the moment a campaign is named.
MemoSight 2.0 addresses the next difficulty: understanding what a dashboard says. Embedded in Marketing Cloud Intelligence, it offers role-based AI recommendations and natural-language questions. A marketing executive and a campaign manager can approach the same information with different priorities. Its appeal is access to an answer within an existing working environment.
MIX-IQ tackles budget allocation through marketing mix modeling and scenario simulation. Agencies and in-house teams can explore proposed spending changes and send outputs into their dashboards. Together, these offers extend a consulting practice into software subscriptions. CampTag’s annual pricing scales with users and workspaces; MIX-IQ’s scales with brands and data complexity.
A forecast has not saved a dollar
One custom application reveals more about the company’s approach than a catalogue of platform badges. For a business process services provider, Decision Foundry built a shared tracker for automation projects and opportunities. As the program expanded, its status lived across spreadsheets, delivery trackers, and conversations. Leadership needed a dependable view of what was working and what to attempt next.
The application separates realized savings from projected savings. An automation still in testing cannot contribute to the realized total. If an hourly cost input is missing, the cost-saving field stays blank. Client feedback shaped successive versions, including customer-level views and opportunity scoring. The early brief also favored simplicity: leave out notifications and add capabilities when stakeholders actually requested them.
This is something a reader can copy without buying anything: keep expected gains separate from delivered gains, attach every calculation to real inputs, and let users review working versions. The distinction matters when a convincing pilot is competing for funding with a process that already runs in production.
The engineer stays
Decision Foundry also offers embedded engineers who work inside customer operations and continue optimizing after deployment. That proximity is its proposed advantage over a brief-and-handover engagement: an engineer sees the workaround that never made it into the requirements document. Its competitive case rests on combining that delivery model with expertise across Salesforce and the surrounding data stack.
The economics are those of professional services plus software. Clutch lists a $25,000 minimum project and rates of $100-$149 an hour, useful directory indications rather than a quote. Managed AI operations are also offered on monthly retainers. A buyer should connect those costs to a defined workflow, its current effort, and a measurable improvement.
As an inference from that model, the fit weakens when a team cannot give engineers access to its systems, provide reliable inputs, or assign someone to approve changes. A simple reporting need may also require less machinery. Decision Foundry’s most persuasive proposition is narrower and more useful: find where existing tools stop helping, then do the engineering that gets the work moving again.