Marketing Automation Statistics Updated November 2026

Human Written & Fact Checked · Updated

102 Marketing Automation Statistics for 2026

Your automation dashboard can look successful while answering the wrong question. A click is not an order, attributed revenue is not incremental profit, and software adoption does not tell you how much of a customer journey is automated.

This collection separates current publisher benchmarks for ecommerce messaging from an explicitly dated historical survey of automation use and difficulties. Read the evidence by trigger, channel and denominator. It is designed for evaluating a workflow, briefing a story or checking a benchmark, instead of estimating a universal market size.

Headline figures

  • In Ascend2's February 2024 panel, 58% used automation for email marketing. (Ascend2 and Research Partners, Mar 2024)
  • Only 9% of Ascend2's February 2024 respondents described their customer journeys as fully automated. (Ascend2 and Research Partners, Mar 2024)
  • Data quality questioned 52% of Ascend2's February 2024 respondents. (Ascend2 and Research Partners, Mar 2024)
  • In Ascend2's February 2024 survey, 28% rated their automation strategy very successful. (Ascend2 and Research Partners, Mar 2024)
  • Klaviyo's 2026 benchmark puts average abandoned-cart email revenue at $6.77 per recipient. (Klaviyo, Oct 2026)
  • Welcome email revenue reached $13.27 per recipient in Klaviyo's top decile. (Klaviyo, Oct 2026)
  • Top-decile abandoned-cart SMS clicks reached 18.5% in Klaviyo's 2026 benchmark. (Klaviyo, Oct 2026)
  • Automations accounted for 2% of Omnisend customer email sends in 2025. (Omnisend, Jan 2026)
  • Automations generated 30% of Omnisend customer email-attributed revenue in 2025. (Omnisend, Jan 2026)
  • Omnisend reported 6.46% conversion for back-in-stock automations in its 2025 dataset. (Omnisend, Jan 2026)
  • Omnisend's automated SMS earned $0.74 in attributed revenue per send in 2025. (Omnisend, Jan 2026)
  • Automated push conversion was nearly 10× scheduled push conversion in Omnisend's 2025 dataset. (Omnisend, Jan 2026)

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Where was marketing automation used in the historical survey?

Automation is a collection of jobs, not a single installed capability. A dated survey helps describe those jobs, but cannot establish today's adoption rate.

Which communication and content tasks were automated?

Email and social applications were prominent in Ascend2's historical panel. The remaining responses describe several operational uses, instead of a single mutually exclusive channel choice. These figures concern respondents reporting a use, not the share of work completed automatically. A company can select several applications while still relying on manual review, creative production or audience preparation. Read this as a map of possible workflow coverage. It does not measure the installed market share of vendors or the proportion of businesses using automation worldwide. The period counts: this is a historical survey baseline, not a fresh estimate of current adoption.

Which targeting and journey-support tasks were automated?

The survey also covered targeting, forms, lead handling and workflow support. Those tasks belong to different parts of the customer journey and should not be treated as interchangeable software categories. A workflow visualization response describes planning or execution support; a lead-scoring response describes prioritization. Neither establishes that customer relationship management records are complete or that a team uses artificial intelligence. When applying this baseline to an audit, first name the business event, the available customer permission and the team responsible for exceptions. Then compare like-for-like applications. Multiple responses are possible, so adding these percentages would not produce an adoption total.

How complete and usable were automated journeys?

Respondents distinguished journey coverage from platform usability. Feeling that a tool makes journey building easy does not establish that the resulting journey is full or commercially effective. The extent responses describe how much of a journey respondents believed was automated. The agreement responses concern the ease of building effective journeys with their platform. These are separate survey questions with different meanings, even when their percentages happen to match. For implementation planning, document where a customer moves from an automated flow to a person and what happens when an event is missing.

What limited marketing automation performance?

Better orchestration begins with usable information and a clear decision process. Buying another feature will not, by itself, resolve the operational problems described in this historical panel.

What improvements did marketers put first?

Respondents wanted improvements across prospect discovery, information quality and execution. These are stated priorities, not measured benefits already delivered by a platform. An intention to reduce costs cannot be converted into an observed cost saving. A goal involving integration also says nothing about the number of systems a business connects successfully. Use the list to organize discovery interviews and identify which outcomes need a local baseline. The survey allows overlapping needs, so the figures are not slices of a budget. They show where respondents wanted to improve, not what buyers should spend.

Which obstacles made automation difficult?

The panel reported difficulties with information, planning and hands-on delivery. The difficulty question describes perceived obstacles instead of audited technical failures. These remaining responses complement the data-quality result in the takeaways. Integration problems may warrant checking event definitions and identity rules before expanding messaging. Resource constraints may instead call for fewer workflows with plainer ownership. Neither diagnosis follows automatically from a survey percentage; a local review must establish which problem exists. HubSpot's later survey concerns broader marketing and a different measurement question.

How successful did respondents consider their strategies?

Respondents generally classified their strategies using broad success categories. The answers express confidence in a strategy, not independently measured financial performance. The remaining categories below sit alongside the very-successful result in the takeaways. This survey does not establish a standardized return on investment, a profit margin or a causal comparison with firms that do not automate. Before translating perceived success into a purchase decision, define the operational result that counts locally: fewer unresolved exceptions, better delivery timing or more reliably attributed orders. Compare that result with a documented baseline. A favorable opinion can be useful qualitative context while still leaving the commercial evaluation unfinished. Keep both forms of evidence visible during a review.

How much revenue did automated email flows generate?

A benchmark is useful only when the trigger and denominator match your workflow. Klaviyo's original platform data separates flow types and performance groups; it does not promise the same result for another store.

How did cart and browse email revenue compare?

  • Cart top decile: $13.70. (Klaviyo, Oct 2026)
  • Browse average: $2.08. (Klaviyo, Oct 2026)
  • Browse top decile: $4.32. (Klaviyo, Oct 2026)

Klaviyo reports different revenue per recipient for cart and browse flows. These dollar benchmarks describe attributed revenue among platform customers, with an average and a top-decile comparison for each trigger. The cart average appears in the takeaways; the remaining comparisons follow below. A shopper who leaves an item in a cart has taken a different action from someone who merely views a product. That difference in eligibility limits what a cross-flow comparison can prove about message quality. Use a matched trigger, similar product economics and a consistent attribution window when assessing your own program. Revenue per recipient is neither revenue per send nor profit after discounts, returns and operating costs.

How did welcome, post-purchase and win-back flows perform?

  • Post-purchase average: $1.80. (Klaviyo, Oct 2026)
  • Post-purchase top decile: $2.77. (Klaviyo, Oct 2026)
  • Welcome average: $5.75. (Klaviyo, Oct 2026)
  • Win-back average: $0.82. (Klaviyo, Oct 2026)
  • Win-back top decile: $1.60. (Klaviyo, Oct 2026)

The flow benchmarks vary across onboarding, repeat-purchase opportunities and reactivation. Each average and top-decile value is reported in dollars per recipient, not as a promised return on spending. The welcome top-decile benchmark is already in the takeaways. Customer eligibility differs across these flows, so their revenue values should not be read as a controlled contest between message formats. A post-purchase message can serve order support even when direct attributed revenue is modest. A win-back audience may be harder to engage because purchase intent has weakened. Evaluate the workflow against its intended job, then check the commercial denominator. Platform benchmarks help frame that discussion without replacing an experiment or a local profitability calculation.

How much did top-performing cart email revenue vary by category?

  • Hardware: $35.24. (Klaviyo, Oct 2026)
  • Home/garden: $28.76. (Klaviyo, Oct 2026)
  • Automotive: $27.48. (Klaviyo, Oct 2026)
  • Electronics: $24.72. (Klaviyo, Oct 2026)

Klaviyo's industry comparisons show that top-decile cart email revenue per recipient varies by merchandise category. A category-specific reference is more informative than applying the same dollar target to every store. These values describe the top-performing group for the stated metric, not the typical business in each industry. Product price, purchase frequency, margin and customer mix can affect the relationship between a recovered order and attributed revenue. The source does not supply a causal adjustment that removes those differences. Choose a comparable category before discussing performance gaps, and retain the performance-group label when sharing a benchmark. A high revenue figure may coexist with high acquisition or fulfillment costs, which this comparison does not measure.

What did automated message engagement look like?

Clicks indicate interaction, not necessarily a purchase or a satisfied customer. Keep channel, trigger and performance group attached to every engagement benchmark.

What were email flow click rates?

  • Cart average: 6%. (Klaviyo, Oct 2026)
  • Cart top decile: 11.3%. (Klaviyo, Oct 2026)
  • Browse average: 5.6%. (Klaviyo, Oct 2026)
  • Browse top decile: 9.8%. (Klaviyo, Oct 2026)
  • Post-purchase average: 5.1%. (Klaviyo, Oct 2026)
  • Post-purchase top decile: 10.5%. (Klaviyo, Oct 2026)
  • Welcome average: 6.5%. (Klaviyo, Oct 2026)
  • Welcome top decile: 13.3%. (Klaviyo, Oct 2026)
  • Win-back average: 2.8%. (Klaviyo, Oct 2026)
  • Win-back top decile: 5.8%. (Klaviyo, Oct 2026)

Klaviyo reports email click rates separately for each automated flow. The pairs below show the average and top-decile benchmarks, preserving the trigger that produced the interaction. A higher rate can reflect audience intent as well as message execution. Before drawing conclusions, check delivery quality, the intended action and how the platform counts clicks. These rates are not order conversion rates. A support-oriented post-purchase flow may direct customers toward information instead of another transaction. Compare equivalent workflows over a consistent period and retain the performance group when sharing the result.

What were SMS flow click rates?

  • Cart average: 10.3%. (Klaviyo, Oct 2026)
  • Browse average: 8.6%. (Klaviyo, Oct 2026)
  • Browse top decile: 15.6%. (Klaviyo, Oct 2026)
  • Welcome average: 10%. (Klaviyo, Oct 2026)
  • Welcome top decile: 18.3%. (Klaviyo, Oct 2026)

SMS click benchmarks also vary by trigger and performance group. Klaviyo's measures below concern message interaction; they do not describe the fraction of the entire subscriber base that bought something. The cart top-decile figure appears in the takeaways. Channel comparisons require care because eligible audiences, consent and customer intent may differ from email audiences. Do not infer that switching a customer to text will reproduce a platform benchmark. Audit link tracking, delivery and the downstream action before treating a click as evidence of success. Revenue and opt-out behavior should be considered separately. The source's precise measurement window is not disclosed on the cited page, which limits direct comparison with a separately dated campaign export.

Why should click benchmarks retain an industry label?

  • Home/garden cart: 6.5%. (Klaviyo, Oct 2026)
  • Hardware browse: 6.5%. (Klaviyo, Oct 2026)

Klaviyo provides industry-specific examples for home and garden cart email and hardware browse email. They illustrate why an overall flow benchmark may not be the best comparison for a particular merchant. These are average click rates for the named flow and industry, instead of top-decile performance or revenue measures. Preserve both labels when using the values in a dashboard. The similar reported values do not establish similar buying behavior, basket size or profitability. They describe interaction with messages at different points in shopping. A useful internal review would compare the same category, trigger and counting method before considering creative changes. If those conditions cannot be matched, use the external benchmark as directional context and explain the uncertainty alongside it.

How did automated email compare with scheduled campaigns?

Omnisend's ecommerce data shows why send volume alone is a poor guide to commercial contribution. The comparison is observational: behavior-triggered audiences are selected differently from scheduled campaign audiences.

How did email revenue per send differ?

  • Automated revenue/send: $2.87. (Omnisend, Jan 2026)
  • Campaign revenue/send: $0.18. (Omnisend, Jan 2026)

Omnisend reports higher attributed revenue per automated email send than per scheduled campaign send in its annual dataset. The send-share and revenue-share results are presented in the takeaways. A triggered message reaches customers after a qualifying behavior; a scheduled campaign may reach a broader audience. That selection difference prevents this comparison from proving what would happen if a business simply replaced its campaign calendar with automations. The figures below use sends as the denominator, so do not merge them with Klaviyo's recipient-based benchmarks. A profitability review also needs delivery costs, incentives, returns and incremental demand. The report provides a useful operating comparison, while leaving those additional questions for the merchant to investigate.

How did email engagement and conversion differ?

  • Campaign opens, 2024: 26.6%. (Omnisend, Jan 2026)
  • Higher automated opens: 24%. (Omnisend, Jan 2026)
  • Stronger automated clicks: 6×. (Omnisend, Jan 2026)
  • Higher automated conversion: 19×. (Omnisend, Jan 2026)
  • Campaign opens, 2025: 30.7%. (Omnisend, Jan 2026)

The report gives scheduled campaign open-rate context alongside relative engagement and conversion comparisons for automation. Relative differences are multiples or percentage increases, not percentage-point changes. The historical campaign open rates describe separate annual observations. They do not establish that the same customer population or tracking conditions remained unchanged. The automation comparisons likewise do not isolate a causal effect of software adoption. Treat opens as a platform-reported engagement signal and examine downstream behavior before attaching commercial meaning to them. A relative conversion advantage also needs the original denominator to become an expected order count. When reporting these figures internally, preserve whether each is an absolute rate, a relative lift or a multiple.

Which automated email occasions stood out?

  • Cart/welcome order share: 76%. (Omnisend, Jan 2026)
  • Birthday order value: $744.37. (Omnisend, Jan 2026)

Omnisend identifies different strengths for cart, welcome, stock alerts and birthday messages. The conversion benchmark for stock alerts is presented in the takeaways; the other observations below use different outcome measures. An order share, a conversion rate and an average order value answer separate questions. Their values cannot be ranked as if they measured the same kind of performance. Cart and welcome journeys address recognizable moments of intent, while an availability alert reaches someone with a reason to revisit a product. A high birthday order value does not imply a large number of orders or a higher profit margin. Select a workflow using customer relevance, permission and operational readiness, then evaluate its intended outcome with a consistent measure.

What do SMS and push benchmarks add?

Multichannel automation needs a separate measurement discipline for each channel. More messages, more attributed revenue and more profitable incremental demand are different outcomes.

How much revenue did automated SMS flows generate?

  • Cart average: $4.48. (Klaviyo, Oct 2026)
  • Cart top decile: $8.69. (Klaviyo, Oct 2026)
  • Browse average: $1.04. (Klaviyo, Oct 2026)
  • Browse top decile: $2.10. (Klaviyo, Oct 2026)
  • Welcome average: $3.33. (Klaviyo, Oct 2026)
  • Welcome top decile: $7.07. (Klaviyo, Oct 2026)
  • Hardware cart top decile: $28.27. (Klaviyo, Oct 2026)

Klaviyo reports SMS revenue per recipient for cart, browse and welcome flows, plus a category-specific top-decile example. These are attributed dollar amounts within its customer sample. The same trigger can serve different audiences across channels, and the costs of delivery differ. Keep the recipient denominator attached when comparing these figures with a merchant's own reporting. The hardware example concerns cart messages in the named category, not a general SMS target. Top-decile values show a performance group instead of the expected result of activating a template. A channel decision still needs permission, customer experience, unsubscribes and incremental margin alongside the attributed revenue comparison.

How did SMS volume and campaign outcomes change?

  • SMS volume growth, 2025: 40%. (Omnisend, Jan 2026)
  • Campaign SMS revenue/send: $0.15. (Omnisend, Jan 2026)
  • SMS volume growth, 2024: 31%. (Omnisend, Jan 2026)
  • UK campaign click-to-order: 5.1%. (Omnisend, Jan 2026)
  • Global campaign click-to-order: 0.97%. (Omnisend, Jan 2026)

Omnisend reports SMS growth and commercial outcomes in its annual ecommerce dataset. Its source also warns that an operating-system update inflated late-year click tracking, likely through automated activity. That tracking caveat counts when interpreting the UK and global campaign click-to-conversion figures below. They are not clean evidence of differences in human intent, nor a controlled comparison of countries. The automated SMS revenue-per-send result is already in the takeaways; its scheduled counterpart appears here. Growth in platform message volume is also distinct from market growth because it can reflect changes in customer activity or sample composition. Preserve these limitations when using the figures to frame a channel plan.

How did automated push compare with scheduled push?

  • Push volume growth: 11%. (Omnisend, Jan 2026)
  • Higher automated push opens: 37%. (Omnisend, Jan 2026)
  • Automated push ROI advantage: 7×. (Omnisend, Jan 2026)

Omnisend reports a push-volume increase and relative advantages for automated push messages. The nearly-tenfold conversion comparison appears in the takeaways and should retain its approximate qualifier. The remaining relative measures below describe comparisons reported by the publisher. Its return-on-investment multiple does not come with a detailed underlying cost definition on the cited page, so it should not be converted into a profit forecast. Automated push eligibility and customer behavior may also differ from the scheduled audience. The publisher's report and announcement disagree on an absolute push conversion figure; this article excludes that disputed value. Read the retained measures as platform observations and test channel economics against your own costs and customer response before expanding delivery.

Glossary

Methodology and sources

Every figure on this page comes from the organisation that produced it: regulators, statistics offices, public bodies, research institutes, and companies reporting their own data or surveys. Each one links to the original report or dataset and carries its release date. Survey results keep their population and fieldwork period, and financial figures keep the measure the producer used. Figures from different producers are not added together or ranked against each other. The page is reviewed monthly and updated when a producer releases newer data.