Using Research in Content Marketing: Brand Strategy and Results

How to use research in content marketing: we break down verified data and event context, plus practical takeaways for brands, agencies, and the advertising market.

Semrush turned one-off research into a continuous growth channel by building a program with four content formats and distributed responsibility across teams. After moving from episodic 80-page PDF reports to regular publications, the company gained thousands of unique visitors without paid promotion, hundreds of sign-ups, and measurable new customer acquisition. We break down how the process works and what's applicable for brands in the Russian market.

How to use research in content marketing?

Before launching the program, Semrush published one or two major reports a year—whenever an idea came up and time allowed. The result was predictable: no planning system, no process owner, no repeatability. Each research project started from scratch, and competitors often beat them to market with similar data.

The turning point came when the company realized that keeping audience attention, traffic, and citations required not just one strong publication, but a steady stream of materials with predictable quality. This meant assigning an owner in the content team and allocating resources in the data analytics department to support ongoing production.

Even unique content like original research quickly becomes a commodity as soon as competitors see its value

For Russian brands, this means: if you plan to launch research as a marketing tool, budget not just for a one-time project, but allocate team resources for at least a quarter ahead. Without clear role distribution between marketing, analytics, design, and email teams, the project will stall at the idea stage.

Four formats for producing research

Semrush identified four categories of research, each with its own process and level of team involvement:

• Research involving data science. Requires technical briefing, engineering time, and a formalized request intake process. Most resource-intensive, but delivers data that competitors don't have access to.
• Collaborations with external experts. The company brings in industry analysts—for example, worked with Kevin Indig, who brought his own perspective on the data and helped expand reach within niche communities.
• Research conducted by marketers in-house. Surveys, lightweight analytics without engineering resources. Enable quick response to trends.
• Co-branded research with other companies. Most labor-intensive, but delivering maximum reach. The joint research with LinkedIn, combining Semrush's data on AI tool citations and LinkedIn's data on content engagement, became the company's most viral piece: LinkedIn promoted it, media outlets republished it, and influencers and customers shared it.

For brands in Russia, co-branded research is particularly valuable: it reduces the burden on internal teams and opens access to a partner's audience. The key is selecting companies with overlapping but distinct audiences, so the data complements each other.

How to select research topics

Semrush plans topics a quarter in advance, using five filters: industry trends, business priorities, product roadmap, customer needs, and sales team feedback. The core criterion is alignment with the company's positioning and messaging.

Example: Semrush promotes the idea that combining SEO and AI visibility is the best approach to organic growth. This perspective directly connects to the product's value proposition, so research on AI citations strengthens the narrative and campaigns.

Another source of topics is user interviews. Semrush's content and product marketing lead conducted weekly calls with customers and noticed a recurring question: why is content often cited but the brand isn't mentioned? The company published research with Kevin Indig that answered this demand.

For Russian brands, the rule is straightforward: identify which research already exists in your niche and find an angle no one has covered. Then ensure your content delivers concrete value to your audience: a checklist, a decision-making takeaway, or a recommendation.

Production process and accelerating launch

Semrush's main challenge at the start was speed. Ideas languished in the backlog for months, the company missed opportunities to become the first source of data, and competitors published materials faster.

The solution: formalizing the request intake process, standardizing briefs, and distributing tasks based on research category. For research requiring data science involvement, a clear intake process was established. Lighter studies were handed to marketers to launch independently, without waiting for engineering resources.

Key takeaway: every publication must contain not just data, but interpretation—why this matters, what to change, how to apply it. Data without context is just noise.

Checklist for launching a research program

• Assign an owner in the marketing team and allocate resources from the analytics or data science department.
• Align with design, email marketing, and campaign teams on support priorities: they need to understand the expected impact.
• Build a quarterly topic plan based on business priorities, customer requests, and gaps in existing research.
• Segment research by team involvement level and create a separate process for each category.
• Verify that each publication answers a specific audience question and proposes action, rather than just presenting numbers.
• Develop a distribution plan before launch: email campaigns, social media posts, media pitches, partner content.
• Define success metrics: reach, citations, registrations, comments from target audience, media mentions.

How to Distribute Research

Semrush uses multiple channels simultaneously: email newsletters to its subscriber base, social media posts with unique hooks tailored to each platform, pitches to journalists and industry publications, content partnerships (the company shares data with media outlets that create their own materials based on it).

The goal is to extend the lifespan of each research project beyond a single publication. Data is repackaged into posts, infographics, webinars, and sales case studies.

For the Russian market, it's important to consider: distribution channels depend on the industry and audience. B2B brands see traction in Telegram channels and niche media, B2C in social networks and through blogger advertising. But the core principle remains the same: plan distribution before launch, not after.

How to Measure Results

Semrush avoids two extremes: measuring everything or measuring nothing. Research projects rarely optimize for direct sales conversion, so the company tracks intermediate metrics: organic traffic to the research page, number of registrations through the download form, backlinks and media mentions, comments and reposts from target audience representatives.

Revenue (new MRR, cross-sell MRR) is tracked where possible, but it's not the primary goal. The program's effect accumulates across multiple publications, and it requires time.

For brands in Russia, this means: don't expect direct sales from the first study. Evaluate brand awareness, media mentions, organic traffic growth, inquiries from media and partners. These signals indicate the program is working, even if customer conversion is delayed.

What this means for the Russian market

Semrush's experience applies to brands operating in segments with high competition for attention: marketing technology, fintech, e-commerce, education. The key condition is the availability of data that can be transformed into insights for your audience: platform statistics, client project results, industry trends.

Entry barriers include the need for a team with analytical expertise, willingness to allocate resources on an ongoing basis, and understanding that results won't come after the first publication, but through systematic effort. However, in an environment where AI tools are reprocessing existing content, original data remains one of the few ways to stand out.

Frequently asked questions

How often should you publish research to make the program work?

Semrush moved from one or two reports per year to a steady stream of publications. The minimum frequency for the program is one research study per quarter to maintain audience attention and create a repeatable process.

Can you launch research without a data science team?

Yes, if you use lightweight formats: audience surveys, analysis of public data, collaborations with external experts. Semrush created a separate category of research that marketers can conduct independently, without engineering resources.

What metrics show that research was successful?

Organic traffic to the content page, number of sign-ups, backlinks, media mentions, comments from your target audience. Direct sales are tracked but not the primary goal: the effect accumulates through a series of publications.