- \n
- The first hour of trading carries a median high to low range of 41.2%, twelve times the range of hour 168. A quote posted at launch is pricing a different asset from the one that exists a week later.<\/li>\n
- Volume, not price, is the variable that collapses first. Across 753 listings, median daily volume fell to 23% of day one by day 30 and 9% by day 90. Month one accounted for 59.4% of all volume traded in the first ninety days.<\/li>\n
- A book under thirty days old is the thinnest book in the market. In a live snapshot of 1,254 order books, 76.2% of month-one listings could not absorb a $50,000 market sell inside 1,000 price levels.<\/li>\n
- Matched on turnover, a token listed within ninety days carried 3.3 times less depth and quoted 1.8 times wider than a token that had traded for more than two years at the same daily volume.<\/li>\n
- The \u201cfree\u201d market maker deal is the expensive one. At the 166% annualised volatility a new listing actually shows, a standard 1.5%-of-supply token loan with three call tranches is worth 51% of the loan notional. No cash leaves the treasury, so nobody budgets for it.<\/li>\n
- Memecoins keep their volume and everything else does not: median day-90 volume was 0.50 times day one for memecoins against 0.08 times for the rest. That figure describes memecoins that survive, and on Pump.fun 4.55% of all tokens ever created were still trading at ninety days.<\/li>\n
- Exchanges now police the relationship. Binance\u2019s market maker guidelines, published 25 March 2026, require issuers to disclose their market maker\u2019s identity, legal entity and contract terms, and ban profit-sharing and guaranteed-return arrangements.<\/li>\n
- Tight quoting travels with better outcomes, deeper books do not, and neither is price support. We tested both and report the result that did not help our case alongside the one that did.<\/li>\n<\/ul>\n
![\"Panel](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/06-numbers-panel-300x169.png\")
Nine numbers a founder should read before listing day. Sources as dated in the panel.<\/figcaption><\/figure>\n What does a market maker actually do after a token listing?<\/b><\/h2>\n
Most founders meet market making as a line item in a listing budget. An exchange asks who is providing liquidity, a firm is introduced, a contract is signed, and the token goes live. What the contract actually buys is easy to describe and hard to do: somebody stands in the market and offers to trade with anyone who shows up, in both directions, at a price they publish in advance, for as long as the mandate runs.<\/p>\n
That obligation looks trivial on day one, when a thousand people want to trade the token and the order book fills itself. It becomes the whole job in week five, when the announcement has been forgotten and the only reason a bid exists at all is that somebody is paid to post one.<\/p>\n
Six things sit inside the mandate. None of them is moving the price.<\/p>\n
![\"Six-card](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/10-six-jobs-after-listing-300x169.png\")
The six jobs a market maker does once the token is live. Framework: TDMM.<\/figcaption><\/figure>\n The first is quoting both sides, continuously, inside an agreed spread and for an agreed share of the session. The obligation is uptime and symmetry, not direction. A market maker who is only ever bidding is not making a market, they are accumulating, and a market maker who is only ever offering is distributing.<\/p>\n
The second is carrying inventory. A quote is a promise to trade, and a promise to trade requires having both the token and the stablecoin to trade with, on every venue, at the same time. Inventory is what separates a market maker from a router. It is also the single largest cost in the business and the thing most contracts are vague about.<\/p>\n
The third is keeping one reference price. A token listed on five venues with no shared mid is five markets, and the gaps between them are harvested by people who are faster than the issuer\u2019s market maker. Our own snapshot found a median 15.5 basis point gap between the highest and lowest venue mid for the same young token, and a 3.0 times difference between the widest and tightest venue spread. That work is the subject of a separate article on cross exchange market making<\/span>.<\/p>\n
The fourth is managing risk through events. Unlocks, further listings, exchange incidents and airdrop claims are scheduled or semi-scheduled shocks. A desk that widens before them and sizes down through thin sessions keeps quoting. A desk that does not gets run over and pulls the book, which is exactly the moment the market needs it.<\/p>\n
The fifth is reporting. Spread held, depth posted, uptime achieved, inventory position, venue by venue, on a cadence the treasury can check against public order book data. An issuer who cannot verify the report is not buying liquidity, they are buying a story.<\/p>\n
The sixth is conduct. No wash trades, no volume targets, no price promises. This used to be a matter of taste. Since March 2026 it is a matter of exchange rules, and since October 2024 it has been a matter of criminal law in the United States.<\/p>\n
Why is the day after a token listing the hardest day?<\/b><\/h2>\n
Because the token has no price history, no natural two-way flow, and a crowd of holders whose cost basis is either zero or a private round.<\/p>\n
To measure this rather than assert it, TDMM pulled daily and hourly candles for every USDT spot pair on Gate, removed tokenised equities, leveraged products and stablecoins, and kept the 1,462 crypto pairs that remained. Of those, 784 recorded their first session inside the 1,000-day window to 25 September 2026, which makes that session a listing we can measure from. 753 have at least ninety-one sessions of history. Every figure below is a median across that cohort, with each token indexed to its own first session so no single large launch drives the shape.<\/p>\n
The day-one numbers are severe. The median listing traded through a high to low range equal to 94.8% of its closing price on its first day. The quartile boundaries were 53.6% and 160.4%, so a range of half the token\u2019s value is the good case. Median close against median open on day one was plus 22.3%, which is the pattern that produces the screenshots and the disappointment in roughly equal measure.<\/p>\n
Inside that day, the shape is steeper still.<\/p>\n
![\"Line](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/01-first-168-hours-volatility-300x169.png\")
The first hour is the widest hour a token will ever have. Source: TDMM analysis of Gate hourly candles, 66 listings, 25 Sep 2026.<\/figcaption><\/figure>\n The median high to low range inside hour one was 41.2%. By hour twenty-four it was 5.7%. By hour 168, the end of the first week, it was 3.3%. The first hour is twelve times as wide as the same token one week later.<\/p>\n
This is the part of the job that is hard in a way no software solves by itself. A market maker quoting in hour one is pricing an asset whose volatility is an order of magnitude higher than the asset it will be in seven days. Quote too tight and the inventory is gone in minutes, picked off by whoever is fastest. Quote too wide and the exchange\u2019s market maker programme obligations are breached and the price aggregator shows a token nobody can trade. The correct answer is wide bands and small size, tightened on a schedule as realised volatility falls, and it is a schedule that has to be decided before the bell rather than improvised during it.<\/p>\n
Volume is concentrated in the same window. Across the hourly cohort, 18.5% of all week-one volume traded in the first twenty-four hours and 35.5% in the first forty-eight. A third of the first week happens before most of the team has slept.<\/p>\n
The liquidity cliff nobody budgets for<\/b><\/h2>\n
Here is the finding that should change how a listing budget is built. The price decline of a new token is widely discussed. The volume decline is not, and it is faster, larger and more consequential.<\/p>\n
![\"Bar](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/02-volume-cliff-300x169.png\")
The volume cliff: attention leaves long before the token does. Source: TDMM analysis of Gate spot market data, 753 listings, 25 Sep 2026.<\/figcaption><\/figure>\n Measured as a multiple of each token\u2019s own first-day volume, the median listing traded 0.64 times day one at day seven, 0.23 times at day thirty, 0.09 times at day ninety and 0.03 times at day 365. Put another way, by the first anniversary the median listing trades 3.3% of the volume it did on its opening day.<\/p>\n
The distribution of attention inside the first quarter is just as lopsided. The median listing did 3.8% of its first-ninety-day volume on day one, 20.4% in week one and 59.4% in month one. Only 40.6% of the quarter\u2019s trading is left for months two and three combined.<\/p>\n
This is what the word \u201cliquidity\u201d actually means in a post-listing context, and why the timing of a market making mandate matters more than its size. The period when a market maker is least necessary is the period most contracts are written for: launch week, when a crowd is already trading. The period when a market maker is the only thing between the token and an empty book is day thirty to day ninety, when the crowd has gone and the token has to look investable to somebody who was not there for the announcement.<\/p>\n
A twelve-week engagement signed for a launch expires at precisely the moment it starts to matter.<\/p>\n
What does the order book of a newly listed token actually look like?<\/b><\/h2>\n
Price and volume are visible to anyone. The order book is not, and it is where the story is.<\/p>\n
On 25 September 2026 TDMM took a single simultaneous level-two snapshot of 1,254 Gate USDT order books, 1,000 price levels a side, and scored each one for quoted spread, notional depth inside 1% of mid on each side, and the realised cost of walking the bid side with a market sell. Grouping those books by how long the pair has traded on the venue produces the clearest picture of the post-listing liquidity problem we have seen.<\/p>\n
![\"Bar](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/04-order-book-by-age-300x169.png\")
A month-old listing is the thinnest book in the market. Source: TDMM level-2 snapshot, Gate spot, 25 Sep 2026 05:31 UTC.<\/figcaption><\/figure>\n \n\n
\n \n Age since first session<\/p>\n<\/td>\n
\n Pairs<\/p>\n<\/td>\n
\n Median spread<\/p>\n<\/td>\n
\n Median 1% bid depth<\/p>\n<\/td>\n
\n Ask over bid<\/p>\n<\/td>\n
\n Depth per $1m of 24h volume<\/p>\n<\/td>\n
\n Cannot absorb a $50k sell<\/p>\n<\/td>\n<\/tr>\n
\n \n 0 to 30 days<\/p>\n<\/td>\n
\n 21<\/p>\n<\/td>\n
\n 52.3 bps<\/p>\n<\/td>\n
\n $823<\/p>\n<\/td>\n
\n 0.77<\/p>\n<\/td>\n
\n $4,168<\/p>\n<\/td>\n
\n 76.2%<\/p>\n<\/td>\n<\/tr>\n
\n \n 31 to 90 days<\/p>\n<\/td>\n
\n 10<\/p>\n<\/td>\n
\n 12.9 bps<\/p>\n<\/td>\n
\n $3,061<\/p>\n<\/td>\n
\n 0.99<\/p>\n<\/td>\n
\n $20,448<\/p>\n<\/td>\n
\n 60.0%<\/p>\n<\/td>\n<\/tr>\n
\n \n 91 to 180 days<\/p>\n<\/td>\n
\n 24<\/p>\n<\/td>\n
\n 31.6 bps<\/p>\n<\/td>\n
\n $1,757<\/p>\n<\/td>\n
\n 0.89<\/p>\n<\/td>\n
\n $39,119<\/p>\n<\/td>\n
\n 83.3%<\/p>\n<\/td>\n<\/tr>\n
\n \n 181 to 365 days<\/p>\n<\/td>\n
\n 104<\/p>\n<\/td>\n
\n 19.0 bps<\/p>\n<\/td>\n
\n $1,886<\/p>\n<\/td>\n
\n 1.00<\/p>\n<\/td>\n
\n $21,192<\/p>\n<\/td>\n
\n 82.7%<\/p>\n<\/td>\n<\/tr>\n
\n \n 1 to 2 years<\/p>\n<\/td>\n
\n 256<\/p>\n<\/td>\n
\n 18.0 bps<\/p>\n<\/td>\n
\n $1,219<\/p>\n<\/td>\n
\n 0.91<\/p>\n<\/td>\n
\n $18,412<\/p>\n<\/td>\n
\n 81.2%<\/p>\n<\/td>\n<\/tr>\n
\n \n 2 years and over<\/p>\n<\/td>\n
\n 839<\/p>\n<\/td>\n
\n 31.3 bps<\/p>\n<\/td>\n
\n $3,708<\/p>\n<\/td>\n
\n 0.94<\/p>\n<\/td>\n
\n $23,526<\/p>\n<\/td>\n
\n 57.3%<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Three things stand out.<\/p>\n
The youngest books quote the widest. A median 52.3 basis point spread on a month-old listing against 31.3 for a token that has traded more than two years is a cost paid by every single participant on every single trade, including the treasury when it eventually needs to transact.<\/p>\n
The youngest books are the shallowest relative to their own activity. Normalising depth by each pair\u2019s own 24-hour volume removes the obvious objection that big tokens have big books. On that basis a month-old listing carried $4,168 of depth inside 1% for every $1 million of daily turnover, against $23,526 for a token trading more than two years. That is 5.6 times thinner per dollar of activity.<\/p>\n
The youngest books are lopsided. The ask side of a month-one listing held only 0.77 times the notional of the bid side, against roughly 0.94 for mature tokens. A thin offer is why new listings gap upward on modest buying and why the chart of a launch so often looks like a spike rather than a market.<\/p>\n
The comparison that survives scrutiny<\/b><\/h2>\n
The bucket table has an honest weakness: the older group trades less, and depth per dollar of volume flatters a quiet token. So we ran the comparison again with the confound removed. For each listing under ninety days old, we found every token that had traded more than two years and did between half and twice its 24-hour volume, and compared against the median of that matched group.<\/p>\n
![\"Bar](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/05-exit-cost-by-age-300x169.png\")
What it costs to sell $50,000 of a token, by how long it has traded. Source: TDMM level-2 snapshot, Gate spot, 25 Sep 2026.<\/figcaption><\/figure>\n \n\n
\n \n At a comparable $179,018 a day<\/p>\n<\/td>\n
\n Listed under 90 days<\/p>\n<\/td>\n
\n Trading over 2 years<\/p>\n<\/td>\n<\/tr>\n
\n \n Median depth inside 1% of mid<\/p>\n<\/td>\n
\n $1,233<\/p>\n<\/td>\n
\n $6,013<\/p>\n<\/td>\n<\/tr>\n
\n \n Median quoted spread<\/p>\n<\/td>\n
\n 19.8 bps<\/p>\n<\/td>\n
\n 12.7 bps<\/p>\n<\/td>\n<\/tr>\n
\n \n Pairs compared<\/p>\n<\/td>\n
\n 31<\/p>\n<\/td>\n
\n 31<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
At the same daily turnover, the young token carries 3.26 times less depth and quotes 1.78 times wider. The gap is not an artefact of size. It is the absence of anybody whose job it is to stand there.<\/p>\n
The cost of that absence is measurable in basis points. Walking the visible bid side with a $50,000 market sell cost a median 629 basis points on a book under thirty days old, against 78 basis points on a book more than two years old. And that figure is generous to the young cohort, because it is computed only on the books that could absorb the order at all. Three in four could not.<\/p>\n
What the evidence says happens to new listings<\/b><\/h2>\n
TDMM\u2019s cohort is one venue. It is worth checking the shape against the two largest published studies of listing outcomes, because when independent datasets built by different people with different methods land in the same place, the finding is probably real.<\/p>\n
![\"Grouped](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/09-listing-outcomes-compared-300x169.png\")
Two independent datasets, the same conclusion. Sources: CoinGecko Spot CEX Report 2026 (updated 9 Apr 2026); CryptoRank (21 Jul 2026); TDMM (25 Sep 2026).<\/figcaption><\/figure>\n CoinGecko\u2019s Spot CEX Report 2026, updated 9 April 2026, tracked new listings on major centralized exchanges since 1 January 2025. It found that across the top twelve venues an average of 32% of newly listed tokens record positive price action immediately after listing, only 25% remain in the green after thirty to fifty-nine days, and by the end of twelve months fewer than 10% of listed tokens on most top exchanges remain above their initial listing price. The per-venue spread is wide: Upbit had the best immediate performance with 67% of its new listings in the green, followed by Binance and OKX at 50%, and every one of Upbit\u2019s new listings went underwater by the 300 to 329 day mark.<\/p>\n
CryptoRank, publishing on 21 July 2026, took a different cut: the 113 tokens launched between 2024 and 2026 that reached a market capitalisation above $100 million. It found 93% trading below their token generation event price, with a median return of minus 95.7%. Eight of the 113, or 7.1%, were above breakeven. CryptoRank named four of them: HYPE at plus 1,519%, ONDO at plus 101.4%, EVA at plus 20.3% and NIGHT at plus 16.5%.<\/p>\n
TDMM\u2019s own cohort produces 30.4% still above the first close at day thirty, 23.9% at day sixty and 9.7% at day 365. The measurement windows differ slightly and the venue differs entirely, and the numbers are within a few points of CoinGecko\u2019s. The median price path runs 0.88 times the first close at day seven, 0.74 at day thirty, 0.46 at day ninety and 0.15 at day 365. The median drawdown from the day-one high to the ninety-day low was minus 85.7%.<\/p>\n
![\"Two](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/03-price-path-after-listing-300x169.png\")
What the median listing does to the people who bought it. Source: TDMM analysis of Gate spot market data, 753 listings, 25 Sep 2026.<\/figcaption><\/figure>\n None of this is an argument that market making fixes the price. It is an argument about what the market maker is standing in front of. A desk that takes a mandate on a newly listed token is taking inventory risk on an asset whose central tendency is a steep decline in both price and volume, and any contract written as though that is not true is mispriced for one of the two parties.<\/p>\n
The structural cause is well documented. Binance Research, writing in May 2024, put the market capitalisation to fully diluted valuation ratio of the 2024 launch cohort at 12.3%, the lowest of the preceding three years, and cited a Token Unlocks estimate that roughly $155 billion of tokens would unlock between 2024 and 2030. In an illustrative sample of recent launches it noted circulating supplies as low as 6% and none exceeding 20%. A token that floats 10% of its supply into a thin book and then releases the rest against it over three years has an arithmetic problem that no amount of quoting solves. The market maker\u2019s job is to make sure the problem is priced in an orderly market rather than discovered in a gap, which is where the token exit strategy<\/span> and treasury<\/span> disciplines connect to this one.<\/p>\n
Memecoins, fair launches and the same problem in a different shape<\/b><\/h2>\n
Memecoins are usually discussed as if they were a different asset class with different physics. On the liquidity numbers they are not. They are the same problem arriving faster and from a different direction.<\/p>\n
A conventional token launch goes from private rounds to a centralized exchange listing with a thin float. A memecoin usually goes the other way: it is born on a launchpad, price-discovered by a crowd on a bonding curve, graduated into a decentralized exchange pool, and only then, if it survives, courted by a centralized venue. By the time a memecoin gets a CEX listing it already has a price, a holder base and a chart.<\/p>\n
That changes the day-one shape. In TDMM\u2019s cohort, the 97 listings matching CoinGecko\u2019s meme-token category had a median day-one high to low range of 68.5%, against 102.6% for the other 656. Arriving with a price already discovered elsewhere makes the first session less violent, not more.<\/p>\n
![\"Grouped](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/07-memecoins-vs-rest-300x169.png\")
Memecoins keep their volume. Everything else does not. Source: TDMM analysis of Gate spot daily candles with meme-token membership from CoinGecko, 25 Sep 2026.<\/figcaption><\/figure>\n The striking difference is what happens afterwards. At day ninety, the median memecoin was still trading 0.50 times its first-day volume. The median of everything else was trading 0.08 times. Memecoins retained roughly six times more of their launch activity. They were also slightly more likely to be above their first close at ninety days, 27.8% against 18.9%, on near-identical median drawdowns of minus 84.2% and minus 85.8%.<\/p>\n
That result comes with a caveat large enough to need stating plainly. CoinGecko\u2019s meme-token category is ranked by market value, so matching against it selects memecoins that lived. The honest reading is that a memecoin which survives to be worth categorising keeps its traders far better than a conventional token does, not that the average memecoin does well.<\/p>\n
The average memecoin does not do well at all.<\/p>\n
![\"Horizontal](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/08-memecoin-funnel-300x169.png\")
The memecoin funnel: 18.67 million launches, 850,000 survivors. Source: CoinGecko Research, study updated 23 Jun 2026.<\/figcaption><\/figure>\n CoinGecko Research examined all 18.67 million tokens created on Pump.fun between 14 January 2024 and 18 June 2026, in a study updated 23 June 2026. It found that 68.67% recorded their last trade on the same day they were created. Same-day and next-day deaths together accounted for 14.99 million tokens, or 80.37% of all launches. About 1% graduated to an external decentralized exchange such as Raydium. Only 4.55%, some 850,000 tokens, survived longer than ninety days, and CoinGecko says plainly that this cohort is the most likely to understate true lifespan because activity after graduation on external venues is not captured.<\/p>\n
Graduation is not survival. A token that fills its bonding curve and seeds a liquidity pool has an automated market maker, which is a very different thing from having a market maker. A constant-product pool will always quote, but it quotes a price determined entirely by its own reserves, it has no view on where the asset trades elsewhere, and it cannot widen when a large seller arrives. The moment a graduated memecoin gets a centralized listing, it has an order book that nobody is standing in, and the numbers in the order book section of this article start to apply to it.<\/p>\n
For a memecoin team, the practical implication is narrow and specific. The launch crowd will handle price discovery, and there is no point paying anyone to help with that. What has to be paid for is the fortnight after the crowd leaves and the month after the CEX listing, when the pool and the book disagree with each other and nobody is reconciling them. That is a market making problem, and it is the one TDMM is most often called in to solve on memecoin mandates.<\/p>\n
How much does market making cost after a token listing?<\/b><\/h2>\n
Two structures dominate the market, and the difference between them is not a matter of price. It is a matter of who owns the token\u2019s upside.<\/p>\n
The retainer, sometimes called market making as a service.<\/b> The issuer lends both the token and the quote currency to the market maker as working inventory, pays a recurring fee for the trading activity and the infrastructure, and gets the full loan back when the contract ends. The issuer keeps the upside on the tokens and carries the capital risk on the inventory.<\/p>\n
The token loan with a call option.<\/b> The issuer lends a slice of supply, usually expressed as a percentage of total supply, and grants the market maker call options over those tokens at strikes above the reference price, typically in tranches. At expiry the market maker either returns the tokens or exercises. No fee is paid. The market maker\u2019s compensation is the option value and the trading profit.<\/p>\n
The second is overwhelmingly the more common structure for a new listing, for a reason that is easy to understand and expensive to ignore: it costs nothing today. There is no invoice, no monthly line item, nothing to put in a budget. It is described in pitch decks as aligned, because the market maker only makes money if the token goes up.<\/p>\n
It is aligned. It is also not free, and the size of the number is the point.<\/p>\n
![\"Line](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/11-call-option-cost-300x169.png\")
The “free” market maker deal is the most expensive one. Method as stated in the source line.<\/figcaption><\/figure>\n Take a worked example with every assumption stated. A token with one billion total supply lists at a $0.10 reference price. The issuer lends 1.5% of supply, 15 million tokens, notional $1.5 million, for twelve months. The market maker receives call options over those tokens in three equal tranches struck at 1.25 times, 1.50 times and 2.00 times the reference price.<\/p>\n
To price those options you need a volatility input, and this is where most issuer-side analysis quietly fails, because the number people reach for is the volatility of an established token. TDMM measured it directly instead. Across 750 listings, annualised close-to-close volatility over days eight to ninety-eight after listing had a median of 166%, with a quartile range of 128% to 218%.<\/p>\n
At 166% volatility, a 4% risk-free rate and a twelve-month tenor, those three tranches are worth $764,723 on Black-Scholes. That is 51.0% of the loan notional.<\/p>\n
![\"Grouped](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/12-structures-compared-300x169.png\")
![\"Table](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/15-exchange-requirements-300x169.png\")
![\"Timeline](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/19-conduct-line-300x169.png\")
![\"Bootstrap](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/14-liquidity-is-not-price-support-300x169.png\")
![\"Bar](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/13-cross-venue-dispersion-300x169.png\")
![\"Five-stage](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/16-ninety-day-runbook-300x169.png\")
![\"Comparison](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/17-coverage-compared-1-300x169.png\")
![\"Seven](\"https:\/\/tdmm.io\/insights\/wp-content\/uploads\/2026\/09\/18-seven-questions-300x169.png\")