GetResponse AI Market Strategy Report - Email Marketing Service

Answer Capsule

GetResponse holds a narrow but real position in AI-generated recommendations for email marketing services, with valid recommendation coverage of 7.17% in September 2026. The brand appears in AI answers at a 10.36% presence rate but converts only a fraction of that presence into actual recommendations, and almost never earns top-three placement. GetResponse's clearest strength is a positive sentiment profile with no negative mentions recorded, while its clearest weakness is the absence of meaningful recommendation placement against category leaders. The largest opportunity lies in converting existing neutral and positive references into valid recommendations across the discovery prompts where the brand already surfaces.

Who This Report Is For

This report is for marketing leadership and growth teams at GetResponse evaluating how AI search surfaces currently recommend the brand in email marketing service discovery conversations.

Report Card

Executive Summary

GetResponse holds a limited but measurable position in AI-generated recommendations within the email marketing service category. The September 2026 benchmark shows GetResponse with a raw mention presence rate of 10.36%, appearing in 52 of 502 qualified observations. However, valid recommendation coverage stands at just 7.17%, meaning the brand is recommended in only 36 of those observations. This gap between presence and recommendation conversion is the central finding for GetResponse.

The sentiment profile is favorable. GetResponse recorded 40 positive mentions, 12 neutral mentions, and zero negative mentions across the qualified sample, producing a net sentiment score of 0.7692. No AI surface framed GetResponse negatively in the September 2026 sample, which provides a clean foundation for building recommendation strength.

The strongest platform signal comes from Perplexity, where GetResponse achieved its highest valid recommendation coverage at 20.90%, with a rank-one rate of 1.49%. Google AI Mode also contributed meaningful coverage at 10.64%. By contrast, ChatGPT, Gemini, and Copilot produced minimal or zero recommendation activity, indicating significant platform-level gaps.

The weakest cluster is the only cluster with qualified observations: Best Email Marketing Service Discovery. Within this discovery cluster, GetResponse appears mostly as a secondary or tertiary option. The brand's average recommended rank of 5.9 places it well outside the top-three positions that drive buyer consideration, and its top-three rate of 0.80% is among the lowest in the tracked set.

GetResponse is visible enough to be named in AI answers but is not yet positioned as a brand AI systems actively recommend. The evidence suggests a recommendation conversion problem rather than a pure awareness problem.

What GetResponse Is Winning

Questions This Section Answers

• Where does GetResponse show its strongest evidence-backed AI recommendation performance?
• Which platforms account for most of GetResponse's valid recommendation activity?

GetResponse's clearest evidence-backed win is its sentiment profile. The brand recorded zero negative mentions across all six tracked AI platforms in September 2026, with a net sentiment score of 0.7692. This is a stronger sentiment position than several larger competitors, including Mailchimp at 0.7383 and Constant Contact at 0.5926.

Perplexity represents a meaningful recommendation pocket. GetResponse achieved 20.90% valid recommendation coverage on Perplexity, with 14 valid recommendations from 67 observations. This is the brand's strongest platform-level performance and suggests some AI surfaces are more willing to recommend GetResponse than others.

Google AI Mode also shows a functional recommendation base. GetResponse recorded 15 valid recommendations across 141 observations on this surface, a 10.64% coverage rate. These two platforms account for the majority of GetResponse's valid recommendation activity.

The brand also holds a narrow but real presence in the discovery cluster. GetResponse appears in 52 qualified observations, giving it more raw presence than Campaign Monitor (Marigold) at 40 mentions and AWeber at 22 mentions. This presence provides a base to build from, even if recommendation conversion remains low.

Where GetResponse Has the Clearest AI Visibility Gaps

Questions This Section Answers

• What explains the gap between GetResponse's presence and its valid recommendation coverage?
• Which competitors displace GetResponse in discovery prompts where it appears?
• How does GetResponse's top-three placement compare with category leaders?

GetResponse's most significant gap is the conversion of presence into valid recommendations. The brand appears in 52 observations but is recommended in only 36, a conversion pattern that lags the category leaders. Brevo, by contrast, converts 451 present appearances into 366 valid recommendations, and ActiveCampaign converts 419 into 330.

Top-three placement is nearly absent. GetResponse holds a top-three rate of just 0.80%, with only 4 top-three placements across 502 qualified observations. The brand's average recommended rank of 5.9 places it far outside the positions where buyers focus their attention. Mailchimp, by comparison, holds a top-three rate of 32.67% and an average recommended rank of 2.86.

Platform coverage is highly uneven. ChatGPT, Gemini, and Copilot produced almost no recommendation activity for GetResponse in September 2026. ChatGPT recorded zero mentions and zero recommendations, Gemini recorded zero of both, and Copilot produced only 3 valid recommendations from 59 observations. This leaves GetResponse absent from three of the six tracked AI surfaces at the recommendation stage.

The competitive displacement is clear. In the discovery prompts where GetResponse appears, the brands AI systems recommend instead are Brevo, ActiveCampaign, Klaviyo, and Mailchimp. These four brands hold valid recommendation coverage between 59.16% and 72.91%, creating a concentrated leadership tier that GetResponse does not currently penetrate.

Biggest Opportunity

Questions This Section Answers

• What is the fastest path to raising GetResponse's overall recommendation coverage?
• What type of evidence could convert GetResponse's positive mentions into broader valid recommendations?

GetResponse's clearest opportunity is converting its existing positive presence on Perplexity and Google AI Mode into broader recommendation coverage across the other tracked surfaces. The brand already earns positive framing when it appears, with zero negative mentions and a 0.7692 net sentiment score. The challenge is not how GetResponse is framed; it is how often the brand is recommended at all.

The path forward is to strengthen the public evidence layer that supports recommendation decisions. GetResponse needs more third-party sources that position the brand as a recommended option for specific email marketing use cases, particularly in the discovery prompts where it already surfaces. If GetResponse can raise its valid recommendation coverage on ChatGPT, Gemini, and Copilot to levels closer to its Perplexity performance, the overall coverage rate would move meaningfully toward the mid-tier of the category.

Competitive Landscape

Questions This Section Answers

• Where does GetResponse rank among tracked brands on top-three recommendation rate?
• Which brands form the concentrated leadership tier GetResponse does not penetrate?

Brevo, ActiveCampaign, and Klaviyo hold the strongest recommendation-stage positions in the email marketing service category, with Mailchimp close behind despite ranking fourth on overall coverage. GetResponse sits in the lower tier alongside Constant Contact, Campaign Monitor (Marigold), and AWeber, with a substantial gap to the leadership group.

Average recommended rank covers rank-eligible recommendations only.

The table shows GetResponse positioned ninth of ten tracked brands on top-three rate, ahead of only Campaign Monitor (Marigold) and AWeber. The brand's average recommended rank of 5.90 is the weakest in the tracked set among brands with rank-eligible recommendations, indicating that when GetResponse is recommended, it appears deep in the answer rather than in a prominent position.

Prompt Evidence

Questions This Section Answers

• How does GetResponse's recommendation outcome vary across the six tracked AI surfaces?
• Which platforms show complete absence of GetResponse in recommendation sets?

Perplexity / Best Email Marketing Service Discovery Prompt: "Which is the best email marketing service?" Result: GetResponse appeared in the recommendation set with positive framing, achieving its strongest platform-level coverage on this surface.

Google AI Mode / Best Email Marketing Service Discovery Prompt: "email marketing platform" Result: GetResponse received valid recommendation credit in a portion of responses, though placement remained outside the top three positions.

Copilot / Best Email Marketing Service Discovery Prompt: "email marketing tools" Result: GetResponse appeared in 8 observations but earned only 3 valid recommendations, with no top-three placement and an average rank of 7.

ChatGPT / Best Email Marketing Service Discovery Prompt: "best email marketing platform" Result: GetResponse recorded zero mentions and zero recommendations, indicating complete absence from this surface's recommendation sets.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompts where GetResponse appears versus where it is absent, identifying which query patterns drive the current 10.36% presence rate and which high-intent prompts return no GetResponse mention at all.

Phase 2: Recommendation Readiness Plan Identify the attributes AI systems associate with recommended brands in this category and compare them against GetResponse's current public positioning to define the gaps preventing recommendation conversion.

Phase 3: Owned Answer Layer Buildout Develop owned content that answers the specific discovery questions where GetResponse should be recommended, structured so AI systems can extract clear positioning statements about the platform's capabilities.

Phase 4: Citation / Authority Layer Development Build third-party citation support from sources AI systems currently trust in email marketing recommendations, focusing on the evidence layer that could move GetResponse from mention to recommendation.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track GetResponse's presence rate, valid recommendation coverage, and top-three placement monthly to measure whether the conversion gap closes across ChatGPT, Gemini, and Copilot.

Why This Matters

AI-generated recommendations are becoming the first filter in email marketing software selection. When a buyer asks an AI surface which platform to use, the brands named in the response gain consideration before the buyer ever visits a vendor website. GetResponse is currently named in about one in ten AI answers but recommended in fewer than one in twelve, and almost never in a position that drives serious evaluation.

Presence alone is not enough. A brand that appears in AI answers without earning recommendation placement is being mentioned but not chosen. For GetResponse, the next move is targeted correction of the prompt, page, and citation layers that determine whether AI systems move the brand from a passing reference to a recommended option.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For GetResponse, this calculation is (40 × 1 + 12 × 0 + 0 × -1) / 52, producing a net sentiment score of 0.7692.

This score matters because unclassified mention counts are misleading. A brand with high raw presence but mostly neutral or negative framing is not in a strong position, even if the mention count looks healthy. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal outcomes. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because the framing of a mention determines whether it helps or hurts the brand.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of GetResponse's AI recommendation visibility in the Email Marketing Service category, drawn from the LLM Authority Index AI Market Discovery Index and supporting metrics aggregation. It is not a client implementation case study.
2. The reporting window is September 2026, with qualified observations collected on September 1, 2026.
3. Six canonical AI/search surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. The benchmark produced 502 qualified observations from 800 source prompt-surface observations, with 487 unique questions represented.
5. The tracked competitor universe includes 10 brands: AWeber, ActiveCampaign, Brevo, Campaign Monitor (Marigold), Constant Contact, GetResponse, HubSpot Live Chat, Kit (ConvertKit), Klaviyo, and Mailchimp.
6. All qualified observations fell into the Best Email Marketing Service Discovery cluster, which captures discovery-and-consideration queries where a buyer seeks a brand recommendation.
7. Stage 0 extraction retained the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed for each observation.
8. A mention is defined as any appearance of a brand in an AI response, in any context, whether positive, neutral, or negative.
9. A valid recommendation is defined as an appearance in a recommendation shortlist where the brand is presented as a suggested option, distinct from a passing reference or comparison anchor.
10. The public benchmark does not measure market share, attributable sales, organic-search ranking, social mention volume, or private channels, and metric movement alone does not establish causality.
11. Percentages are calculated against the qualified observation set of 502, not the 800 raw prompt-surface observations collected.
12. GetResponse's small observation base on some platforms means percentage movement can reflect small absolute changes; rates should be interpreted with appropriate caution.

See How AI Is Recommending Your Brand

The public benchmark shows where GetResponse stands in AI-generated recommendations, but the aggregate percentages do not reveal which high-intent prompts the brand wins or loses, which competitors take the recommendation when GetResponse is not chosen, or which external sources shape those answers. A company-specific AI visibility audit maps prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy, turning the benchmark's directional signals into a concrete action plan for the prompts and surfaces that matter most.