Digital market analysis: search, social and review data

Questions this report answers

How much search interest does our category attract in each country, and how seasonal is it?
Which needs, features and problems come up most often in searches and reviews?
What share of brand searches do we get compared with our competitors?
What do customers praise and criticise in our reviews and in competitors' reviews?
How is sentiment about the brand or category moving, and what triggered the changes?
Which websites, marketplaces and communities influence buying decisions in the category?
Where do visitors leave our website, and which traffic sources bring buyers rather than browsers?

When you need it

The most common use is an early read on a market before a larger decision. Search data show within days whether a category has real interest in a new country and language, which makes them a useful first filter before a survey or a market entry study. The same data support competitor benchmarking, product development through mining reviews for unmet needs, and reputation monitoring after a campaign, a recall or a pricing change.

The digital footprint of a market varies widely between countries. According to Eurostat, 63.6% of EU-27 enterprises with ten or more employees used social media in 2025, compared with 83.8% in the Netherlands and 41.5% in Bulgaria. On the consumer side, Eurostat shows the share of Bulgarians aged 16–74 who bought online rose from 30.9% in 2020 to 51.2% in 2025. A thin online presence in one country therefore does not mean a small market, only a less visible one.

Digital analysis is the wrong choice when you need representative measures: awareness among people who never search for the category, market shares, or attitudes of non-users. Those require a survey or brand health tracking. Very small B2B niches also produce too little public conversation to analyse.

Sample table of contents

Executive summary
the main signals and what they mean for your decision
Scope and sources
countries, languages, keywords, platforms and period covered
Search demand
category interest, seasonality and trend by country
Search intent map
query clusters by need, feature and problem
Share of search
brand interest against competitors over time
Social listening
volume, channels, topics and influential sources
Sentiment and its drivers
what moves opinion in either direction
Review mining
ratings and recurring themes from marketplace and app-store reviews
Web analytics review
traffic sources, landing pages and conversion paths
Competitive digital footprint
websites, content, social presence and paid search visibility
Implications
recommendations for product, content, channels and market entry

Methodology and sources

Search demand

We build a keyword universe for each language from seed terms, autocomplete suggestions and competitor pages, researched locally rather than translated, because people search differently in each market. Monthly volumes come from search-engine planning tools, and queries are grouped by intent to produce a search demand analysis. Volumes are estimates, so they are used to compare terms, months and countries rather than as exact counts; they can also feed a market sizing study or our TAM/SAM/SOM calculator.

Social listening and sentiment

Social listening collects public posts, forum threads and comments with refined queries that filter out noise, such as brand names that are also everyday words. Automated sentiment analysis is then checked by manual coding of a sample in every language, since models misread sarcasm and local slang.

Reviews, analytics and ethics

Reviews from marketplaces, app stores and booking platforms are coded into themes and set against star ratings to show which issues pull scores down. Your own web analytics are reviewed through read-only access. We use public data within platform terms, build no profiles of individuals and paraphrase quotes so authors cannot be traced, in line with the GDPR.

What you receive

Report in PDF with findings and recommendations
Keyword universe in Excel with volumes, intent clusters and seasonality
Monthly share-of-search and sentiment charts
Coded review and social themes with anonymised examples
Optional dashboard for ongoing monitoring
Workshop with marketing, e-commerce and product teams

How the project runs

Briefing — 2–3 days to agree markets, competitors and questions
Keyword and query building — 3–5 days per language
Data collection from search, social, review and analytics sources — about 1 week
Coding, sentiment validation and analysis — about 1 week
Report and workshop — 2–3 days
Optional monthly monitoring against the baseline

Hypothetical example for illustration

Worked example

Example: a hypothetical Portuguese online retailer of outdoor furniture is considering the Netherlands and Belgium as its next markets and wants evidence before investing in local-language websites.

The search analysis shows strong spring seasonality in both countries, with a steady share of queries about compact sets for balconies and about weather-resistant materials. Mining competitor reviews on the main marketplaces reveals two recurring complaints: damage in transit and unclear assembly instructions. Social conversation in the category is limited and mostly about delivery problems, so it adds little beyond the reviews.

The retailer decides to launch first in the Netherlands ahead of the spring peak, leads with its balcony range, upgrades its packaging, adds video assembly guides, and builds Dutch-language content around the main query clusters. Share of search against the three leading competitors becomes the baseline for measuring progress, alongside a fuller competitor analysis.

Common mistakes and how to avoid them

Treating online voices as the whole market. People who post are a vocal minority, so triangulate with surveys or sales data.
Translating keywords instead of researching them. Each language has its own phrasing, and literal translations miss the real queries.
Trusting automated sentiment without checks. Manual validation of a sample shows how far the model can be relied on.
Counting mentions without context. A spike may come from one viral post or from bots, so check the sources behind it.
Reading search volume as sales. Interest is not purchase; combine it with conversion data before forecasting.

Who it suits

Suitable for	Why
E-commerce brands entering a new country	Search and review data show demand and expectations within weeks
Consumer brands monitoring reputation	Tracks topics and sentiment between survey waves
Product teams planning a new range	Review mining reveals unmet needs and recurring complaints
Hotels, restaurants and travel businesses	Reviews drive bookings, and themes can be compared by property
B2B firms benchmarking competitors	Compares websites, content and search visibility side by side

Frequently asked questions

How long does a digital market analysis take?

Usually two to four weeks. A single country and language sits at the shorter end. Each additional language needs its own keyword research and its own sentiment validation, and a long historical period of social data adds collection and cleaning time.

What affects the cost of a digital market analysis?

The number of countries and languages, the size of the keyword universe, the platforms and time period covered, how much manual coding is needed and whether you want ongoing monitoring or a dashboard. Outline your markets and competitors and we will put together a quote.

How accurate are search volume figures?

They are estimates from search-engine tools, rounded and sometimes grouped across similar terms. They are reliable for comparing queries, countries and months, but not as exact counts. We cross-check them with trend data and, where needed, with desk research on the category.

Can digital analysis replace a survey?

For some questions, yes: the topics people raise, the problems they report and how interest changes over time. It cannot measure awareness among non-searchers, market shares or the attitudes of a representative sample. It works best before a survey, to sharpen the questions, or between survey waves.

Is social listening compatible with the GDPR?

Public posts can still contain personal data, so the GDPR applies. We collect only publicly available content within platform terms, report at an aggregated level, never profile individual users, reword quotes so that authors cannot be identified and keep raw data only as long as the project requires.

Do you need access to our own analytics?

Only if the scope includes your website or app. Read-only access is enough, results are reported in aggregate, and access is removed when the project ends. Analysis of competitors' search, social and review presence relies on public data alone and needs nothing from you beyond their names.

Sources

Updated: 5 Nov 2026

Digital market analysis: search demand, social listening and review mining