Most marketing questions wait in line for an analyst, and the answer lands after the meeting is over. Alli for Self-Serve Answers lets the person with the question ask Ask Alli in plain English, explore the follow-up in Data Explorer, and build the view in Generative Dashboards, all on data your teams already agreed on. Analysts spend their time on the deeper work. People still make the decisions.
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This campaign demonstrated what happens when brand insight, creative discipline, and execution align.
3xSales vs. initial forecast
With Alli, PMG's operating system for business transformation, PMG built a two-phase launch around Gen Z's view of rest as self-expression. Creators in the GlowHouse influencer house built early demand, then the For Your Sleepy Head campaign and #SquishTok carried it through Back-to-School. Alli Creative Insights tested the creative in flight so spend stayed on what was working.
200%Increase in brand preference
With Alli, PMG defined who the campaign had to reach, from first-time buyers to experienced traders. The team paired a one-day studio shoot with a generative AI desert environment, built around the image of a sandboarder reading shifting terrain, and launched across digital and out-of-home placements in the UAE.
Read the FXTM story
44%Share of voice of all Games-related social conversation
With Alli, PMG connected more than 50 data sources into one live view of the Games. Alli Creative Insights scored every athlete film and "WIN" asset within hours, Ask Alli gave planners answers on demand, and Alli Brand Equity tied sentiment to sales. Real-time assets went live within minutes of each victory.
Read the Nike storyThe data exists. That’s rarely the problem. The problem is the time between a question and a trusted answer.
A new question comes up in a planning meeting. Someone files a ticket. An analyst pulls the numbers, builds a view, and sends it a few days later. By then the budget call has been made another way, or the meeting has ended without a decision. Next week the same cut of data gets requested again, by someone else, because nobody knew the first one existed.
Meanwhile the analysts who should be modeling and interpreting spend their week pulling and rebuilding. And when media, creative, analytics, and finance finally do bring numbers to the same review, they often bring different versions of performance. The first twenty minutes go to deciding whose number is right.
AI raised the stakes. A general chat assistant answers fast, but it improvises over an export and doesn’t know your definitions. Self-serve only works when the person asking can trust what comes back.
The answer arrives after the decision has been made
How Alli for Self-Serve Answers handles itAsk Alli answers a plain-English question during the meeting, with the data, logic, and source visible
A new question goes to the back of the queue for a new build
How Alli for Self-Serve Answers handles itGenerative Dashboards builds the view from a sentence, a sketch, a screenshot, or a template
Analysts rebuild the same cuts of data every week
How Alli for Self-Serve Answers handles itRoutine questions are answered directly by the people who have them, so analysts get time for modeling and interpretation
The first answer raises a second question, and the second waits too
How Alli for Self-Serve Answers handles itData Explorer lets people filter, compare, and ask the next question in the same place
Each team brings its own version of performance
How Alli for Self-Serve Answers handles itEvery view reads from data under shared definitions in the Semantic Layer, and every dataset links to its approved source
Leaders get another chart, not an explanation
How Alli for Self-Serve Answers handles itData Explorer summarizes what changed and why, and dashboards carry summaries next to the charts
A budget error or a mid-campaign shift is spotted after the money is spent
How Alli for Self-Serve Answers handles itAnyone can check a number while there’s still budget to move
A general AI assistant improvises over a spreadsheet
How Alli for Self-Serve Answers handles itAnswers resolve against the metrics and business rules the business already agreed on
Alli for Self-Serve Answers is a loop that starts with a plain-English question. Ask Alli answers it. Data Explorer is where the follow-up goes. Generative Dashboards turns the view you keep returning to into something the team can share. And a job you’d otherwise repeat every Monday can be described once and delivered where the team works. Every step reads from the same trusted data, so the number in the answer matches the number in the dashboard.
A plain-English question becomes a verified answer, table, or chart. Ask Alli resolves it against shared definitions and shows the data, the logic, and the source.
People filter, slice, and compare across channels, markets, audiences, and dates, with Ask Alli built in for the follow-up. A summary explains what changed and why.
A sentence, sketch, screenshot, or template becomes an interactive dashboard with charts and summaries. Analysts can add Python, SQL, or JavaScript when a view needs deeper logic.
A recurring job is described once. Ask Alli writes the SQL, builds the summary, and sends the draft to Slack for review.
Ask Alli, Generative Workflows
Explore Ask Alli Explore Data Explorer Explore Generative Dashboards
Five moments from the loop, each shown by the decision it improves.
Type the question the way you’d say it out loud. Ask Alli maps it to the shared definitions in the Semantic Layer and returns an answer you can trace back to its source.
What it’s worth. Budget questions get answered in the call, not tabled for next week. Teams using Ask Alli report an 80% reduction in time to insight.
Data Explorer lets people slice and compare connected performance data with point-and-click controls, or ask in plain English through built-in Ask Alli. The next question starts from the last answer, not from scratch.
What it’s worth. The person with the question gets to the answer, and analysts aren’t pulled in for every cut.
Every dataset links back to its approved source and shared definitions. When two numbers disagree, Data Explorer compares the sources directly.
What it’s worth. Meetings spend less time on whose number is right and more on what to do.
Describe what you want to see, or upload a sketch, screenshot, or template, and Generative Dashboards builds an interactive dashboard with KPIs, charts, and filters on your data. Role-based access controls who sees what. Ask for a different cut and it updates.
What it’s worth. A multi-week build becomes a few minutes. Teams using Generative Dashboards report a 90% reduction in reporting time.
Data Explorer turns a raw table into a clear summary and can produce a tighter talk track or a one-slide recap. Dashboards carry summaries alongside the charts.
What it’s worth. Less time explaining the numbers, more time deciding what to do about them.
Built to scale your team’s expertise, not replace it.
Alli answers routine questions, builds the views, and shows its work. Your analysts and data owners keep the sources, the definitions, and the access rules, and they take on the modeling and interpretation only they can do. Marketing leaders, media leads, and finance partners decide what the answers mean and what to do next. Nothing in this loop makes the decision for them.
Ask. Resolves a plain-English question against shared definitions and shows the data, logic, and source
Decide which questions matter, and judge what the answer means for the business
Explore. Filters, compares, and summarizes what changed and why
Check the pattern against what they know about the market, and decide where to dig deeper
Build. Generates the dashboard, and applies role-based access to who can see it
Decide what the team should track, and add Python, SQL, or JavaScript where a view needs custom logic
Deliver. Writes the query, builds the summary, and sends the draft to Slack for review
Review the draft before anything goes out, and decide what happens next
Maintain. Reads from the sources and definitions it’s given
Analysts and data owners set the sources, definitions, and access, and change them on purpose
Self-serve on top of messy, conflicting sources just means more people reaching different conclusions faster. So Ask Alli, Data Explorer, and Generative Dashboards all read from the same trusted data, defined once in the Semantic Layer. A filter one team applies means the same thing for every other team. Technical teams keep control of the sources, the definitions, and who can see what. Everyone else gets direct access to what those sources contain.
Pressure-test a budget question in the meeting and walk into reviews with one version of performance instead of three.
Investigate a mid-campaign shift yourself, find where it’s concentrated, and adjust while the campaign is still running.
Explore trends across platforms, creators, and markets, and test a hypothesis before it goes into the plan.
Hand off the routine cuts of data and spend your time on modeling and interpretation.
See performance from the same data marketing uses, so budget conversations start from agreement.
Compare markets and channels quickly, and catch budget going to the wrong place while there’s time to move it.
Role-based access decides who sees which data, and every dataset links to its approved source.
Explore creator and platform performance across partners in one view.
Most teams get answers three ways: scheduled dashboards in a BI tool, spreadsheet exports, or a request to the analytics team. Each works for some questions. None works well for the one you have right now.
| BI dashboards and reports | Spreadsheet exports | Analyst request queue | Alli for Self-Serve Answers | |
|---|---|---|---|---|
| Best for | Known, recurring views | One-off analysis by whoever has the file | Deeper analysis that needs an expert | The question you have now, and the next one |
| A new question | Wait for someone to build a new view | Pull another export and rebuild the logic | File a ticket and wait | Ask in plain English, filter, or build a view from a sentence |
| Trust in the numbers | Depends on how the view was built | Drifts with every copy | Depends on the analyst | Linked to approved sources and shared definitions |
| Analyst time | Spent building and maintaining views | Spent on reconciliation | Spent pulling repeat cuts | Freed for modeling and interpretation |
| Role of people | Read what was planned for | Do the work by hand | Wait for results | Lead every step, with AI scaling their expertise |
Start with the question your team asks most often and can’t answer quickly. Each entry point connects to the rest of the loop later.
Get it answering that one question first, and see the source behind the answer
Start with Ask AlliDescribe the request in a sentence and see what comes back
Start with Generative DashboardsCompare the two sources and trace the discrepancy
Start with Data ExplorerMove the three most repeated requests to the people who make them
Start with Ask Alli and Data ExplorerBuild the executive summary once, then have the draft delivered to Slack for review
Start with Generative Dashboards and Generative WorkflowsHow Alli gets answers to the people who ask, with analysts and decision-makers in charge.
Alli for Self-Serve Answers is a connected set of Alli products that let people get their own answers. Ask Alli answers questions in plain English, Data Explorer handles the follow-up and the investigation, and Generative Dashboards builds shareable views from a sentence, all on data teams already agreed on.
Teams using Ask Alli report an 80% reduction in time to insight. Teams using Generative Dashboards report a 90% reduction in reporting time. They measure different things: the first is the time from question to answer, the second is the time spent building reports. Results depend on where a team starts.
No. You type the question the way you’d say it out loud, or filter and compare with point-and-click controls. Ask Alli writes the SQL where it’s needed. Analysts who want more control can embed Python, SQL, or JavaScript in a dashboard. Technical teams still own the sources and definitions underneath.
Every request resolves against the metrics and business rules in the Semantic Layer, and you can see the data, the logic, and the source behind each answer. When two numbers disagree, Data Explorer compares the sources directly. If something looks off, you can trace where the number came from.
No. It changes what they spend time on. Routine questions and repeat cuts of data get answered by the people who have them. Analysts keep the sources, the definitions, and the deeper modeling and interpretation that needs their expertise. Dashboards are good for questions planned in advance. This handles the rest.
Not necessarily. Many teams keep a BI tool for standardized, scheduled reporting. Alli handles what comes up in between: the follow-up question, the mid-campaign investigation, and the new view someone needs this week. Data Explorer and Generative Dashboards sit alongside the BI tool rather than forcing a replacement.
No. Dashboards run on approved data connections and shared definitions, and role-based permissions control who can see which data. More people can build and explore without anyone seeing data they shouldn’t. Data and IT teams keep control of sources and access, and everyone else works within what they’re given.
Alli is available to PMG clients. Marketing, media, analytics, and finance teams use the same platform PMG’s experts use, so both sides work from the same data and results. Book a walkthrough, bring a question your team can’t answer quickly today, and we’ll work through it on your data.
Book a self-serve walkthrough and bring the question your team asks most often. We’ll run it on your data, show you where the answer comes from, and build the view you’d have waited a week for. Alli is available to PMG clients.