Make and Make AI Agents help TripleTen reduce ad setup time by 5 to 7x

• Industry: Education & Research

• Use case: Campaign Management

• Country: US

• Company size: 51–200 employees

• Apps used: Google Gemini AI, Google Sheets, Meta, Slack, TikTok, Google Ads, Apify

TripleTen, an online tech education provider, runs a high-volume performance marketing operation, like testing hundreds of creative assets per month across Meta, YouTube, TikTok, and Google. Managing that volume manually was slowing the team down on every front: uploading creatives to ad platforms, monitoring what competitors were doing, and understanding which creative elements actually drove results.

By building three interconnected scenarios in Make, including an elaborate Make AI Agent, TripleTen's marketing team automated the full creative lifecycle, from upload to analysis. 

As a result, they could decrease the time spent on ad setup by up to 7x, reduce creative labeling of 1,000+ assets per year from weeks to seconds, and free up hundreds of hours per month to focus on strategy.

Maksim Epifanov, User Acquisition Lead at TripleTen, explains how Make became the engine behind their creative intelligence operation.

"Given all the results, we will definitely use Make for all our other tasks connected with automation.”

Maksim Epifanov, User Acquisition Lead at TripleTen

The challenges

As TripleTen scaled its marketing operation, three bottlenecks emerged that manual processes simply couldn't keep up with.

No systematic way to monitor trends 

The user acquisition and social media teams wanted to understand what competitors were producing and which formats were gaining traction. But competitive research meant manually browsing ad libraries, screenshotting examples, and sharing them in Slack on an ad hoc basis. There was no scalable, consistent way to track trends across markets or turn that data into actionable direction for creative production.

No visibility into how creative assets perform

TripleTen produced over 1,000 creative assets in 2025 alone. With so many variables influencing performance – format, target audience, pain point, value proposition, call to action – the team had no reliable way to connect creative characteristics to business outcomes like Cost Per Lead, customer acquisition cost, or Return on Ad Spend (ROAS). Manually tagging and sorting each variable of 1,000+ creative assets to identify their individual performance would have taken weeks. Even then, inconsistent human tagging would have made the performance analysis unreliable.

Hours lost to repetitive creative uploads

TripleTen tests hundreds of creative assets every month across multiple ad platforms. Each upload, like creating campaigns, naming ad sets, and assigning creatives, had to be done manually in each platform's ad manager. For a team running at that advertising volume, the process ate up hours that could have been spent on strategy and optimization.

The solution

TripleTen used Make to build three scenarios that together cover the entire creative intelligence pipeline, from publishing to competitive monitoring to performance analysis.

An AI agent for competitive intelligence

To replace ad hoc manual research, TripleTen built a competitor monitoring AI agent in Make. The scenario pulls structured data from Meta Ads Library, TikTok Ads Library, and Google Ads, using Apify to scrape public ad libraries for a defined list of competitors stored in Google Sheets. For each competitor and market, Make extracts raw creative data, including video links, headlines, hooks, call-to-action copy, and descriptions.

A second set of scenarios analyzes that raw data with AI: labeling creative characteristics, categorizing them against TripleTen's internal marketing framework (target audience, value proposition, pain point), and translating content from any language into English. The aggregated output is stored in Google Sheets and summarized in Slack. It surfaces top trends, recurring formats, and standout competitor examples for the creative and social media teams to act on.

"Previously, my user acquisition team manually searched and explored creatives from competitors, then posted examples in Slack with a message like 'hey, let's discuss this.' Now the agent does that work automatically. It's faster, it's aggregated, and it's not just one example."

Maksim Epifanov, User Acquisition Lead at TripleTen

Creative performance analysis powered by Gemini

Using Make, TripleTen also tackles the question every performance marketing team wants to answer: which creative elements actually drive results? Make analyzes their full library of creative assets – videos and banners – across 20 defined parameters, including format, target audience, pain point, unique selling proposition, and call-to-action type.

Make sends each asset to Gemini, which extracts and assigns values for all parameters. That structured data is stored in Google Sheets and joined with actual campaign performance metrics. The result is a systematic analysis that shows, for example, which formats deliver the best ROAS, which audience segments outperform others, and which topics resonate most. 

The team now knows they need to produce more user-generated content and influencer content, that parents outperform other audience segments in their vertical, and that specific pain points leading customers to TripleTen’s services – like concerns about AI replacing jobs – drive stronger engagement than others.

"Tagging creatives shows me exactly which elements drive performance and which fall flat, so I can test more precisely, scale what works, and cut what doesn't."

Polina Zhilkova, Creative Project Manager at TripleTen

One-click creative uploads across ad platforms

The team built a scenario in Make that connects their centralized creative database to multiple ad platform APIs. When a creative asset is ready, a user acquisition manager opens a link, clicks upload, and Make handles the rest: creating the campaign structure, naming ad sets, and uploading the creative with consistent naming conventions. What previously took hours now takes under a minute.

"Automating creative uploads for Meta Ads with Make has been a game-changer for us. It cuts the time spent on routine ad setup by 5–7x, reduces manual errors, and frees up the team to focus on strategy instead of repetitive tasks. It's one of those improvements that scales instantly as campaign volume grows."

Ivan Galenko, User Acquisition Manager for Meta at TripleTen

The results

Make's three scenarios delivered measurable impact across TripleTen's marketing operation:

• 5–7x reduction in time spent on ad setup for Meta campaigns alone, with consistent results at scale

• Hundreds of hours saved per month across the user acquisition team on manual creative uploads

• Creative labeling that previously would have taken weeks to complete manually now runs automatically across 1,000+ assets per year

"I'm using a Make scenario to automate creative uploads to Google Ads. Since we test a lot of videos, doing it manually was too time-consuming. Now, we've got it down to one-click launches!"

Muhu Guseinov, User Acquisition Manager for Google Ads at TripleTen

The marketing team's engine for scale

TripleTen and Make proved a natural fit for a performance marketing team that needed to move fast without losing visibility. Make gave the team the flexibility to connect multiple ad platforms, AI models, and data tools in one place.

The three scenarios TripleTen built make the entire creative strategy more legible. The team can now see what's working, why it's working, and what to build next.

With an SEO content agent and campaign analytics scenarios already in development, TripleTen is extending the same approach across more of its marketing operations.

“We have a lot of things in progress, and we will continue using Make."

Maksim Epifanov, User Acquisition Lead at TripleTen