Deepsolv vs Canva Grow: Who Decides the Next Ad?

A team can produce ten polished ads a day and still guess at which ten. Canva Grow 2.0 (June 25, 2026) helps make, publish and read ads, and proposes refreshes from campaign data (Canva's announcement). Deepsolv ranks the next test using competitor and customer signals as well.

A separate decision sits upstream of making ads: which concept goes next, and why that one.

We build Deepsolv for that upstream decision. This page compares the two by the job each does. It ends with a five-question check you can run on your own ad account in about 30 minutes.

• Choose Deepsolv if your bottleneck is deciding what to test next on Meta. Choose Canva Grow if your bottleneck is producing and publishing the ads.
• Deepsolv turns ad-performance data, competitor activity, customer signals and past ad learnings into a ranked weekly test plan and execution-ready creative briefs.
• Canva Grow reaches Meta, TikTok and LinkedIn. Its AI Ad Tagging feature requires Canva Business or Canva Enterprise.
• A five-question check below tells you in about 30 minutes whether deciding or producing is slowing you down.

Canva Grow is Canva's ad platform for generating, publishing and reviewing paid ads. As of the June 25, 2026 release, it generates static and video ads, bulk publishes to Meta, TikTok and LinkedIn, shows campaigns in a launch dashboard, and consolidates performance in multi-platform reports. AI Ad Tagging labels creative elements. Automatic Refresh Generation proposes new concepts from campaign data. (Canva's announcement)

Canva began the rollout in North America, Australia and the United Kingdom on that date. AI Ad Tagging requires a Canva Business or Canva Enterprise account.

Choose Deepsolv when the question you cannot answer is "what do we test next?" Five facts about our platform decide it.

1. You get a ranked plan, not a pile of options. Our platform output is a ranked weekly creative test plan, with guidance on what to make, skip, improve or stop. You open Monday with an order of work.
2. Competitor activity is an input. We track competitor ads across messaging, angles, offers and formats, so your plan reflects what rivals run. Treat those ads as clues about what to test, not proof of what earns them revenue.
3. Customer words feed the plan. We read comments, DMs, reviews and Reddit for the language buyers use, then turn it into angles.
4. Past learnings carry forward. Brand Brain remembers what worked, what failed and why, so a test you lost in spring does not return in fall.
5. The output is a brief, not a vague idea. Each ranked test comes with an execution-ready creative brief your designers, editors or creators can start from.

We also analyze the numbers that tell you when an ad is tiring: click-through rate (CTR), cost per click (CPC), add to cart (ATC), return on ad spend (ROAS) and ad fatigue.

Canva Grow covers ad generation, bulk publishing, and TikTok and LinkedIn coverage alongside Meta. Those are production and distribution jobs; Deepsolv is built for the planning job ahead of them. Deepsolv's ranked briefs can direct whatever Canva Grow or any other editor produces.

They differ on inputs, outputs and where each sits in the workflow. Deepsolv adds competitor activity and customer comments, DMs (direct messages), reviews and Reddit threads as planning inputs.

What information goes in?

We combine four inputs: ad-performance data, competitor activity, customer signals and past ad learnings. Canva Grow's reports consolidate performance data across platforms, and its refresh feature builds new concepts from campaign data. A plan built on four inputs can disagree with your own dashboard, which is the point. Your best ad may be your best only for the audience you already reach, while customer comments and competitor angles point somewhere new.

What comes out?

A ranked weekly test plan and execution-ready briefs come out of our platform. Grow produces finished ads you can open in the Canva editor. These are different deliverables, so a team can use a brief from us to direct what Grow, or any editor, makes. Our A/B test hypothesis template shows how to write the hypothesis a brief should carry.

Where does the work sit in Meta's structure?

Meta organizes ads into campaigns, ad sets and ads, and sets audience, placements, budget and schedule at the ad set level (Meta Business Help Center). Our recommendation: decide the concept first, then place it in an ad set you can fund. Our test plan sits ahead of that step, and its briefs go to whoever produces the ad.

How do you start and what does it cost?

Deepsolv has no public self-serve price. We scope it to your team and workflow in a personalized demo with our founding team. Canva's prices differ by plan; current prices are on Canva's pricing page as of November 2026.

Run these five tests on your own account. Fail three or more and your bottleneck is deciding; our recommendation is to start with Deepsolv. Pass most and your test plan is solid. Deepsolv still ranks each week's next tests. The thresholds are our rule of thumb, not an industry standard.

1. Concepts with a reason. In Ads Manager, count the distinct concepts you launched in the last 30 days (a concept is a new angle or hook, not a resize). Pass: at least half have a one-line written hypothesis. Fail: fewer.
2. Next three tests. Write your next three tests, with one reason each, in five minutes. Pass: each reason cites a metric, a competitor ad or a customer quote. Fail: any reason is "it looks good" or "we always run this."
3. Competitor angles. Name the main angle each of your three closest competitors runs now, using the Meta Ad Library (Meta's public database of active ads). Pass: you name all three. Fail: you name fewer than three. Our competitor ad volume guide explains what ad counts do and do not tell you.
4. Customer words in live ads. Pull three phrases from reviews, comments or DMs. Pass: at least one appears word for word in a live ad. Fail: none does. Our post-purchase survey questions show one way to collect them.
5. Where the days go. Take your last launched ad and count days spent choosing the concept and days spent making it. Pass: choosing took no longer than making. Fail: choosing took longer.

Related comparison: Deepsolv vs AdCreative.ai.