The State of SalesTech 2026

This is a review of published research on sales technology. It is not a survey. We have not asked anyone anything, and where we eventually do, we will publish the sample size, the fielding period and the questions.

We are stating that at the top because it is the central problem with this category. A great deal of what circulates as sales technology research is a vendor's customer list surveyed about the vendor's product, a composite financial model built from a handful of interviews, or a number that was never a study at all. Distinguishing those from evidence is most of the work, and it is what this report is for.

1. Outbound stopped being a soft discipline

The most consequential change in sales technology over the last two years was not a product. It was three sets of published rules that turned deliverability from a craft into a compliance exercise with numbers attached.

Google defines a bulk sender as anyone sending close to 5,000 messages or more to personal Gmail accounts within a 24-hour period, counts messages from the same primary domain toward that total, and states that senders meeting the criteria at least once are permanently considered bulk senders. It asks senders to keep spam rates reported in Postmaster Tools below 0.10 per cent and to avoid ever reaching 0.30 per cent or higher, at which point a bulk sender becomes ineligible for mitigation until the rate stays below that level for seven consecutive days.

Bulk senders need SPF, DKIM and DMARC, with the policy permitted at none, plus alignment of the From domain with either SPF or DKIM. One-click unsubscribe under RFC 8058 is required for marketing mail at that volume, a mailto link alone does not satisfy it, and requests should be honoured within 48 hours.

The date that matters is not February 2024, when the requirements took effect. It is November 2025, from which Google states it has been ramping up enforcement on non-compliant traffic, with messages experiencing temporary and permanent rejections.

Yahoo asks for a spam rate below 0.3 per cent, calculated on its side from mail delivered to the inbox, which reads lower than a sender's own measurement. It requires SPF, DKIM and a passing DMARC policy for bulk senders, recommends the RFC 8058 method and explicitly accepts mailto, and publishes no numeric bulk sender threshold.

Microsoft applies its requirements to domains sending more than 5,000 emails a day to Outlook.com, enforced from 5 May 2025. Its original announcement said non-compliant mail would be junk-foldered; an update on 30 April 2025 replaced that with a decision to reject, designated 550 5.7.515. Microsoft's own postmaster policy page still carries the older wording, which is a live contradiction between two Microsoft sources.

Any tool that raises sending volume faster than it raises engagement is now operating against published thresholds with published consequences. That is the single most important change in the buying criteria for outbound tooling, and it is absent from almost every comparison in the category.

2. AI in sales: the gain is real and it is not where the pitch says

The most useful measurement published this year came from ICONIQ's go-to-market research, fielded in January 2026 across 147 B2B software companies. It compared companies with more than half of pipeline AI-influenced against the rest.

Conversion from new lead to MQL was eleven percentage points higher. MQL to SQL was eight points higher. Demo to closed won was three points higher. SQL to closed won was one point higher.

The publisher's own conclusion is that AI provides account executives with more, better-qualified opportunities but does not currently change outcomes once deals are in an active cycle.

The Bridge Group's 2026 account executive research, across 158 companies fielded in the first half of 2026, found 57 per cent of reps at quota in the highest AI engagement tercile against 39 per cent in the lowest. The terciles were pre-specified before outcomes were examined and three negative controls were tested, which is unusually careful for this category. The publisher states plainly that the data is observational and that it is not claiming causation.

Both findings point the same way and both carry the same limitation. Companies with more than half of pipeline AI-influenced, or in the top tercile of AI engagement, are not otherwise average companies. Self-selection is doing unknown work in both results.

What the evidence supports is a spending shape rather than a return estimate. The measurable value sits in qualification and volume. There is not yet evidence that it sits in closing.

3. The platform bet moved to quote to cash

Three corporate moves in a single month tell you where the vendors think the friction now is.

On 8 June 2026 Salesforce agreed to acquire m3ter, a consumption metering and rating company, completing on 1 July 2026, price undisclosed, folding it into its revenue management product and citing the flexible usage and outcome-based pricing models needed for the AI era. On 15 June 2026 Salesforce agreed to acquire Fin, formerly Intercom, for approximately $3.6 billion, expected to close in the fourth quarter of its fiscal 2027. On 18 June 2026 HubSpot launched Revenue Hub, positioned explicitly as quote to cash, finally in one place.

The reason is structural. Consumption and outcome-based pricing put a metering problem inside a commercial process designed for fixed-term subscriptions. The approval chain, the quote, the contract and the revenue recognition were all built for a price known at signature. Increasingly it is not.

For buyers, the practical consequence is that metering, rating and quoting are converging into the CRM platform. If those functions currently live in three systems, that architecture is now visibly on the wrong side of a platform decision.

4. The evidence base, and what it costs the industry

This section is the one we would most like to stop writing in future editions.

The statistics that circulate in sales technology are unusually unreliable, and the failure is systematic rather than occasional. Four patterns recur.

Misquotation of a real source

The most-cited forecasting statistic, that sales forecasts are accurate less than half the time, is a misreading of a Gartner finding about confidence: 45 per cent of sales leaders and sellers had high confidence in their organisation's forecasting accuracy. Confidence and accuracy are different quantities. The misquote appears in vendor material, in trade press and in board decks.

Circular citation

One forecasting vendor's benchmarks page sources every figure on it to other blogs, one of which is a competing forecasting vendor, none of which discloses a sample or a method. A separate post from the same vendor attributes a statistic to a 2020 Gartner report while linking to an article about a 2013 study. Two studies seven years apart, presented as one.

A remark that became a benchmark

The figure that 60 to 70 per cent of B2B marketing content goes unused, which has justified enablement purchasing for over a decade, originated as a statement made from a conference stage in May 2013. No sample size, no methodology and no fielding period was ever published, and it has never been replicated by anyone including its own publisher.

Fabrication

During this year's research we encountered a benchmarks page presenting an intent data conversion rate of 21.3 per cent against 8.4 per cent, attributed to a Forrester study that does not exist. The same page cites a vendor report that does not exist and two research organisations that were retired in 2019 and 2020. The figures are already propagating and were returned to us as fact by a search summariser.

Ban the figure, not the domain. Fabricated statistics change their attributed source as they spread, so a blocklist of publishers will not catch them.

5. What the category has never published

Some absences are more informative than the available numbers. Each of the following is something a buyer would reasonably expect to exist, and none does in public.

• Intent data conversion. No vendor, analyst house or academic publishes the proportion of intent-flagged accounts that become opportunities. What exists is vendor-commissioned composite ROI models, satisfaction surveys, relative-lift case studies, and analyst guidance telling buyers to measure accuracy themselves.
• Intent signal accuracy. No provider publishes a false-positive rate, a precision figure or a match rate. There is no accreditation, no standard and no independent audit. The only vendor acknowledgement of the problem attaches no number to it.
• A forecasting head-to-head. No vendor or academic has published a study comparing AI pipeline forecasting against manual roll-up on the same deals over the same periods with a stated method.
• Conversation intelligence coaching evidence. The most-quoted talk-to-listen ratio in sales coaching appears in vendor documentation as established fact with no published method, sample or definition of converting.
• Approval and quote-to-cash cycle time. No verified data exists on approval cycle time, the proportion of deals requiring approval, discount thresholds or CPQ implementation outcomes.
• Enablement effect on ramp. No source publishes onboarding programme design against measured ramp outcome.
• Content utilisation. No measurement from the last three years.
• Cost of replacing a rep. The circulating figures could not be traced to any named dated primary.

We also could not verify a sales technology or CRM market size figure, or an average sales stack size, this year. Both are widely quoted. Neither could be obtained from a primary source in this research pass, and we would rather report the gap than fill it.

6. What is worth doing about it

For buyers, the practical response is not scepticism for its own sake. It is a short set of questions that change the conversation.

• Ask for the sample size and the fielding period on every figure in a vendor deck. Note which ones produce an answer.
• Ask what the product does automatically at a 0.1 per cent complaint rate and at 0.3 per cent. This distinguishes vendors who have operated at scale from those who have not.
• Check your own data volumes against published model minimums before the first demo. It disqualifies part of the shortlist for free.
• Insist on a backtest against your own last four closed quarters for anything predictive.
• Hold out a control group in every pilot, and randomise it if you can. This is the step almost nobody takes and the only one that produces evidence.
• Agree shutdown criteria in writing alongside success criteria.

For the category, the fix is simpler and unlikely. Every vendor in enablement, CRM and conversation intelligence holds instrumented telemetry that would answer the questions listed in section five. Content opens. CRM writes. Meeting duration. Flagged accounts against booked opportunities. None of it has been published.

The first vendor to publish a genuine utilisation or conversion dataset, with a method and the inconvenient findings left in, will own the evidence base for a decade. That is a larger prize than another feature release, and it is sitting unclaimed.

On this report and the next one. This edition is a review of other people's research, and we have labelled every source accordingly. We are aware that a publication documenting the sector's evidence problem has an obligation to meet a higher standard itself. When Sales Hub Media publishes original data, it will carry the sample size, the collection period, the questions asked and the segments, on the report itself, and it will publish findings that do not flatter us alongside findings that do.

This report is a review of published third-party research. It is not original survey data and we do not present it as such. It is not procurement, legal or investment advice.

References

Every figure and legal citation in this article is drawn from the sources below. Where an instrument is proposed rather than in force we say so in the text.

1. Google, Email sender guidelines. https://support.google.com/mail/answer/81126
2. Google, Email sender guidelines FAQ. https://support.google.com/a/answer/14229414
3. Yahoo, Sender requirements and recommendations. https://senders.yahooinc.com/best-practices/
4. Microsoft, Strengthening the email ecosystem: Outlook's new requirements for high-volume senders, published 2 April 2025, updated 30 April 2025. https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/strengthening-email-ecosystem-outlook%E2%80%99s-new-requirements-for-high%E2%80%90volume-senders/4399730
5. Microsoft, Outlook.com postmaster policies and announcements. https://sendersupport.olc.protection.outlook.com/pm/policies.aspx
6. ICONIQ, The State of Go-to-Market in 2026, survey fielded January 2026, n=147, March 2026. https://www.iconiqcapital.com/growth/reports
7. The Bridge Group, AE Models, Motions and Metrics 2026, n=158, fielded Q1 to Q2 2026, 22 June 2026. https://www.bridgegroupinc.com/research/2026-ae-models-motions-metrics
8. Salesforce, Salesforce signs definitive agreement to acquire Fin, 15 June 2026. https://www.salesforce.com/news/press-releases/2026/06/15/salesforce-signs-definitive-agreement-to-acquire-fin/
9. Salesforce, Salesforce signs definitive agreement to acquire m3ter, completed 1 July 2026, 8 June 2026. https://www.salesforce.com/news/stories/salesforce-signs-definitive-agreement-to-acquire-m3ter/
10. HubSpot, Introducing Revenue Hub: quote to cash, finally in one place, 18 June 2026. https://www.hubspot.com/company-news/introducing-revenue-hub-quote-to-cash-finally-in-one-place
11. Gartner, Press release on the State of Sales Operations Survey, forecasting confidence and data quality, 12 February 2020. https://www.gartner.com/en/newsroom/press-releases/2020-02-12-gartner-says-less-than-50--of-sales-leaders-and-selle
12. Forrester, Intent data expectations versus reality, on the Q1 2023 Global B2B Intent Data Survey, 26 October 2023. https://www.forrester.com/blogs/intent-data-expectations-vs-reality-whats-working-and-where-are-the-gaps/
13. Forrester, formerly SiriusDecisions, Summit 2013 highlights: inciting a B2B content revolution, origin of the unused-content figure, May 2013. https://www.forrester.com/blogs/summit-2013-highlights-inciting-a-btob-content-revolution/
14. Salesforce, Einstein data requirements for sales. https://help.salesforce.com/s/articleView?id=ai.einstein_sales_data_requirements.htm
15. Gong, Analyze team performance, published metric definitions, updated 7 January 2026. https://help.gong.io/docs/analyze-team-performance

How we work. This report was researched and written by the Sales Hub Media editorial team. We do not republish press releases. Every number and legal citation is checked against a primary source, which is named and linked above. Where an instrument is proposed rather than in force, we say so. Corrections are made openly on the report itself, never by silent edit. If you believe something here is wrong, write to info@saleshubmedia.com and tell us what and why.