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Marketing Software Articles
80+ Marketing Statistics to Shape Your 2026 Marketing Strategy
2023 Trends: Making Your Marketing Win in Times of Loss
Marketing Software Discussions
Looking for input from the Consumer Insights Platforms category on platforms that genuinely combine survey research with social listening, the combination that mid-size retail brands need to understand both what customers say when asked directly and what they say unprompted on social media, without maintaining two separate vendor relationships.
- Suzy: It provides Suzy Speaks (video interviews), Suzy Live (digital focus groups), and trend monitoring in a single platform. For mid-size retail brands, the combination of quantitative survey capability, qualitative video interviews, and trend monitoring addresses the most common split between a survey tool and a social/trend listening tool.
- Qualtrics Strategy & Research: The platform's Research Hub provides AI-powered search and synthesis across all studies, including external documents, which can incorporate social and external signal data alongside proprietary survey research. The CX and EX integration layer connects survey data to operational metrics, creating the unified customer signal view that retail brands need.
- GWI: GWI's survey-based consumer intelligence covers media consumption, online activities, social platform usage, and channel affinity data, providing the audience behavior signals that retail brands typically use social listening to understand, grounded in a statistically representative panel rather than a social media data scrape. The platform covers which social platforms an audience uses, what content they engage with, and how channel preferences are shifting.
- Discuss: For mid-size retail brands where the most valuable consumer insight comes from in-depth qualitative conversations rather than broad survey data or social monitoring, Discuss provides the qualitative research infrastructure that surfaces the why behind consumer behavior that neither surveys nor social listening fully explains. The AI analysis layer finds themes and correlations across sessions automatically.
- Attest: Attest is described as fast, compliant, and simple enough for operations teams to use without specialist support, which matches the resource profile of mid-size retail marketing teams. The data storytelling layer allows findings to be shared directly with leadership.
For mid-size retail brands that have tried to consolidate survey and social listening into one platform, was the consolidation successful, or did the combined platform cover both use cases less well than two dedicated tools would have? And which insight type drove more actual brand decisions in practice?
In practice the insight that drove more actual decisions for our team was the survey side. Social listening surfaced things we didn't know to ask about but the depth of understanding came from structured questions.
Worth separating two things in your consolidation question. Buying one platform is about vendor overhead and budget. Getting one view of the customer is about whether the two data types can actually be read against each other. GWI is interesting here because its social platform and channel affinity data comes from the same panel structure as the rest, so you're comparing like with like rather than stitching a survey result to a scrape and hoping the populations match.
I’d expect the combined platform to work best when the goal is connecting different types of insight, rather than replacing every capability of two specialist tools. For retail, I think unprompted trend signals would drive more day-to-day brand decisions, while surveys would be most useful for validating why those shifts are happening.
In my experience the survey data drives more actual decisions because it's easier to defend in a meeting, you can point to a specific question and a specific number. Social listening tends to shape hypotheses more than final calls, at least on my team.
Hi G2 community! I am looking for Consumer Insights Platforms for multi-market tracking accuracy. This is for brands that need to understand how consumer preferences are shifting in different demographics simultaneously, and where inconsistent methodology across markets produces incomparable data that cannot be used for global strategic decisions.
- Qualtrics Strategy & Research: The platform supports 100+ question types with consistent survey methodology across markets, and the global distribution via email, SMS, and multichannel delivery ensures methodological consistency. Brand tracking is a named prebuilt solution.
- GWI: GWI covers 50+ markets with 2M+ annual surveys run across four waves per year, providing the current data and trend comparison capability that preference tracking requires. It is uniquely valuable for the Japanese market because it allows comparison with other markets at the same granularity — the like-for-like multi-market comparison that most tools cannot deliver at that geographic specificity. The longitudinal data structure means preference trends are visible over time rather than only at a single point.
- Attest: Attest covers 59 countries with fully localized and translated surveys across 70 languages, with the ability to compare regional groups side by side in the same study. EU data residency and GDPR compliance make it particularly relevant for multi-market studies that include European markets, where data sovereignty requirements add complexity.
- Forsta: Is a full-service enterprise market research platform with global panel access and the methodology depth to run longitudinal tracking studies across multiple markets simultaneously. As a platform used by research agencies and enterprise brands for continuous tracking, Forsta covers the multi-market panel access and consistency requirements.
- Cint: For brands managing research across several markets simultaneously, Cint's breadth of panel supply provides the geographic coverage that single-panel providers cannot match. Cint is a sample and panel sourcing platform rather than a full consumer insights platform; it provides the respondent supply that powers other platforms' research but does not include survey building, analysis, or reporting tools on its own.
For global brands running tracking studies across multiple markets, what has been the most challenging dimension to keep consistent? Is it panel quality and methodology across different countries, survey translation that preserves question meaning across languages, or the analysis framework that allows like-for-like comparison of results?
Survey translation preserving question meaning is consistently the hardest dimension to maintain in our experience. Responses to a question about brand perception in Japanese versus English can reflect translation nuance as much as actual preference differences.
Translation, but not in the way it usually gets discussed. Literal accuracy is the easy part and a decent localisation process handles it. The harder problem is that the same perfectly translated five-point scale gets used differently: some markets cluster toward the middle and avoid the extremes, others reach for the top box readily, and respondents in some cultures lean agreeable toward whatever the question proposes. So your Japan number and your Brazil number can sit fifteen points apart on identical wording and identical underlying sentiment. That's why the GWI point about comparing Japan against other markets at the same granularity matters so much. One consistent instrument fielded the same way everywhere at least holds the bias constant, so movement over time stays readable even where the absolute levels aren't.
Reporting movement against each market's own baseline sidesteps most of this without new tooling. The absolute cross-market comparison is the part that needs caveats, not the trend.
Qualtrics Market Research is heavily reviewed and well suited for tracking changing customer preferences across multiple countries at once, since it's built for large-scale, multi-market research programs.
Looking for input on Consumer Insights Platforms, specifically on ease of insight extraction in a tool where a non-specialist can read the dashboard at the end of the day and actually understand what to do differently.
- Attest: Has intuitive interfaces that even team members without market research experience could navigate easily. The real-time reporting dashboard is described as simple enough that operations teams can interpret results without a data specialist. The data storytelling layer allows findings to be shared with stakeholders without additional formatting work.
- Discuss: The AI analysis layer is specifically described as helping find insights from previous research and identifying valuable correlations — the extraction step that typically requires a trained analyst. The intuitive interface means teams can navigate different research types without requiring qualitative research expertise.
- PickFu: For teams whose primary consumer insight need is fast validation of creative decisions, which product image performs better, which landing page headline resonates more, which packaging concept wins — PickFu's poll format delivers results in minutes with the winner clearly visible without requiring data processing. The format is inherently self-interpreting: a percentage breakdown of which option won, with open-ended comments explaining why.
- GWI: GWI's Agent Spark AI analyst allows team members to query the data in plain English and get explainable answers without requiring research platform expertise, and the search feature means analysts do not need to memorize the survey structure to find what they need. The preset dashboards provide a simplified consumer profile view that is described as easy to share and digest with senior stakeholders without additional formatting.
- Askable: Addresses the participant recruitment and scheduling overhead that typically makes qual research the most time-consuming step — automating the logistics of finding, screening, and scheduling the right respondents so the research team can focus on the conversation and the insight rather than the coordination. For teams without dedicated research operations support, Askable's automated recruitment directly removes the most time-consuming manual step.
For marketing teams that have found a platform where a non-specialist can go from survey launch to actionable insight without a data team, what made the difference? Was it the dashboard design, the AI-generated summary layer, or simply the question format that made the findings self-evident?
The AI-generated summary layer is what made the difference for our team. Not because the underlying data changed but because non-specialists could read the output and actually act on it without a researcher translating it.


