Pull competitor frequency from your CRM
Before you decide which competitors get resources, find out which ones are actually in your deals. Pull your CRM data for the last 6–12 months and ask:
Which competitors show up most often?
Which ones are tied to your biggest losses?
Where are you consistently winning versus losing?
Does the competitive mix change by segment, deal size, or vertical?
This is your ground truth. It should drive your prioritization, not market noise or brand recognition. If your CRM data is messy (which it usually is), supplement it with call transcripts. Tools like Gong are especially useful for catching competitor mentions that never made it into structured fields.
| Competitor | Deals · Last 6 months | Action |
|---|---|---|
| Atlas Cloud Suite | 62 | Named |
| Northwind | 51 | Named |
| Foxtrot | 36 | Named |
| In-house build | 31 | Named |
| Brightline | 22 | Named |
| ▼ ~10 deals / qtr · threshold | ||
| Quartz | 12 | Bucket |
| Vela.io | 9 | Bucket |
| Mosaic | 6 | Bucket |
| Pebble | 4 | Bucket |
| Drift Labs | 2 | Bucket |
Frequency-driven, not noise-driven. A venture-backed startup getting press might show up in 2 deals a quarter. A quiet incumbent might show up in 30.
Define your tier 1 threshold
Tier 1 competitors are the ones that show up frequently enough to warrant a named battlecard and ongoing maintenance. A reasonable heuristic: any competitor that appears in more than 10 deals per quarter deserves a named card.
The number will vary by your deal volume. The point is to set a threshold based on frequency, not on how well-known the competitor is or how much noise they're making in the market. Resource accordingly.
Most teams end up with 5–10 tier 1 competitors. Don't cap it arbitrarily. Use the frequency threshold and let the data tell you where to draw the line.
Why frequency matters more than brand recognition
A tier 1 battlecard takes real effort to maintain: product positioning, updated objection handling, win/loss context. Every card you add is a maintenance commitment. If a competitor is showing up in 2 deals a quarter, that cost isn't worth it. If they're in 30, it obviously is. The threshold makes the decision explicit rather than political.
Group everything else into buckets
Every competitor that doesn't meet your tier 1 threshold goes into a category bucket. This is not a consolation prize. It's a deliberate design choice that makes your CI more scalable and often more useful for reps.
The insight: if you get down to what truly makes your company different, a lot of your competitors start to look the same. They create the same friction in deals. Your response to them is essentially the same. If that's true, one well-built category card is more useful than ten thin named cards with nothing meaningful in them.
The trick to bucketing is to start with the place of pain, not "what category does this competitor belong to in the market" but "what is the problem this type of competitor creates for buyers who are evaluating us?"
Pain · Already paying for one
Incumbent suite modules
Pain · DIY can do this
Spreadsheet & in-house
Pain · Cheaper, narrower
Point-tool challengers
Expect your own company to live in one of these buckets from a buyer's perspective. That's normal, and useful context for your positioning.
How to define your buckets in practice
Three to five buckets is the right range. Fewer than three is too broad: you'll end up with buckets that are so generic they give reps no real guidance. More than five usually means you're over-segmenting, which recreates the problem of too many named cards.
Start with the pain, not the label.
Instead of asking "what category is this competitor in?" ask "what problem does this type of competitor create for buyers evaluating us?" Market category labels ("workflow automation", "data platform") don't map to deal friction. Pain does.
Anchor on your own positioning first.
You can't define buckets without a clear center. Before grouping competitors, articulate what makes you different. The buckets are defined by the threat vector (the way a competitor challenges your positioning), not by market taxonomy.
Group competitors by deal patterns.
Look at objections, buyer behavior, and win/loss reasons, not product features. Two competitors might have completely different products but create identical deal dynamics: same objections, same buyer profile, same close rate against you. That's the same bucket.
Sanity check with someone newer.
Show your bucket definitions to a rep who joined in the last six months. If they can't quickly classify a competitor they've encountered, your buckets aren't clear yet. Clarity is the test.
Keep a running list.
Once something is categorized, reps shouldn't have to figure it out again. Maintain a simple lookup that maps competitor names to their bucket. This can live in your battlecard tool, a Notion page, or wherever reps actually go for competitive info.
Cover the long tail with AI
Below your bucket threshold lives the long tail: competitors showing up in one or two deals a year, niche tools specific to one vertical, regional players, new entrants. You can't build named cards for all of them. You shouldn't try.
This is where AI earns its place in a CI program. Use it to analyze closed-lost data in bulk, identify patterns you haven't categorized yet, and generate on-demand competitive context for the one-off competitor a rep encounters that's not in your battlecard library.
“Summarize closed-lost deals from the last 6 months grouped by competitor. For each competitor, what were the top objections and what did buyers say they valued about their solution? Then identify which competitors seem to create similar patterns in deals and suggest how they might be grouped.”
The output won't be perfect, but it will surface groupings and patterns faster than manual analysis, and often reveals bucket candidates you haven't formally categorized yet.
Frequently Asked Questions
How many tier 1 battlecards should a PMM team maintain?
Most teams end up with 5–10. More than that is usually a sign that the threshold is too low or the prioritization process hasn't been run recently. Each named card requires ongoing maintenance (new product releases, pricing changes, updated positioning), so there's a real cost to every card you add. Use frequency data to set the threshold and let the number emerge from that, rather than deciding upfront how many cards you want.
What if my CRM data on competitors is messy or incomplete?
It usually is. Reps don't always fill in the competitor fields, and when they do, the naming is inconsistent. Start by cleaning the data for the last 6 months: deduplicate competitor names, fill in what you can from memory or CS notes, and mark what's missing. Then supplement with call transcripts from Gong or similar tools, which catch competitor mentions that never made it into CRM fields. You won't get perfect data. You're looking for directional signal, not precision.
How do I know if a competitor belongs in a bucket vs. its own named card?
Run the frequency check. If a competitor is appearing in more than 10 deals per quarter, give them a named card. If they're below that threshold, bucket them. The exception: even low-frequency competitors occasionally warrant named treatment if they show up disproportionately in your biggest deals or in a specific high-value segment. In that case, build a named card but acknowledge it's segment-specific, not general.
Can buckets overlap? Can the same competitor fit in two buckets?
Resist the urge to let competitors live in two buckets. The goal of bucketing is to give reps a single, fast answer: which bucket does this competitor belong to, and what does that tell me about the deal I'm in? If a competitor fits two buckets, the bucket definitions are probably overlapping. Fix the bucket definitions before you try to double-tag competitors.
How often should I revisit my tier structure?
Once per quarter is usually right. Pull fresh CRM data, check if any bucket competitors are now crossing the frequency threshold, and check if any tier 1 competitors are showing up less often. The tier structure should follow the data. Companies pivot, lose market relevance, or get acquired. Your battlecard structure should reflect what's actually happening in your deals, not what was true six months ago.
Does every company need all three tiers?
Small companies with limited deal volume might not have enough data to distinguish tier 1 from tier 2. In that case, start with buckets only and wait until you have enough data to see frequency patterns. The long-tail AI coverage is worth setting up regardless of company size. It handles the random competitors your reps encounter that you can't predict.
Want to see how teams use Hindsight to pull competitor frequency from deal data and keep battlecards current automatically?
See how Hindsight works