Customer data
Customer data
About project
Startup for gamers (beginners and advanced alike). Right now the platform’s focus is on monster games like PUBG, Dota 2 and League of Legends. Currently, the team has launched a new product in the gaming industry: Gosu Voice Assistant for Dota 2 and League of Legends games.
Project goals
At the start of work, organic traffic was 34,000 per month and was predominantly branded, with more than half of the traffic coming from the CIS countries, the rest from countries with poor solvency. Therefore, the main task was to increase the number of the most solvent audience from the USA.
Issues
The service itself runs on a specially designed (self-written) platform, there is also a blog on the Ghost platform (to which we moved from WordPress), and landing pages on Tilda.
The project required a comprehensive approach. It was necessary to correct technical errors (it’s no joke, the site simultaneously uses three solutions that are different in terms of the stack of technologies for displaying content), achieve correct Google indexing and create content in large quantities, while not forgetting to build up link mass.
We were hampered by errors in technical SEO and the lack of landing pages. If we present all our work in stages, then it will look like this:
(Analysis of competitors, search for traffic sources)
(Crowd marketing, Buying links on exchanges, Outreach)
(Preparation of quality and expert content)
(Creating pages to meet user needs)
(Improvement of site navigation, ease of use of the site)
(Expansion of the keyword table)
(Finding and correcting critical errors on the site)
(Optimization of meta-tags, implementation of micro-markup)
Progress
We analyzed the niche and identified the strengths and weaknesses of not only our project but also our competitors. During the analysis, it became clear that the information demand dominates the topic, and the fastest way to get traffic and registrations on the service is to pump the blog with expert content. After all, any gamer wants to learn how to play more effectively, and the Gosu.AI service can help him with this.
We understood that we only needed to create content that would be head and shoulders above the competitors’ articles at the top. It was necessary to re-read dozens of guides from competitors and shovel tons of game semantics. It usually took three to four hours to analyze the niche and collect semantics for a specific article (given that the topics of the articles had already been approved in the media plan).
Beginning players often need comprehensive yet understandable guides, and it is not always easy for them to find quality content that would answer all questions, guides to action, step-by-step instructions, and other tips. Some aspects of games were frankly poorly disclosed by competitors in the issue. We had a chance, and there is a lot of work ahead.
How do we create a content plan?
To draw up a content plan, we assessed the total frequency of key queries for each article and their competitiveness. In such topics, it is necessary to carefully study the intent of the request, and if this is not done, there is a risk of wasting money on the content for nothing.
Stats Pages to Attract Gamers
In this niche, every gamer wants to get statistics for both their games and other players, especially professional players.
We hypothesized that various pages with detailed statistics on weapons, maps, and pro players would be popular with users and able to attract search traffic.
Here are some typical questions that may pop up in a PUBG gamer’s head:
- What weapons are the most effective in the game?
- Where on the map is the best place to land?
We have developed a list of such pages based on demand, and have prepared detailed tasks for developers on their implementation.
Final result
In total, the blog, developed from scratch by the joint efforts of the Rush and Gosu teams, attracted more than 400 thousand visitors from organics.
The articles took the TOP for quite tasty requests:
Let’s draw a final line on the results achieved with two graphs.
The first one is the dynamics of requests from fourth to tenth places:
The second one is the dynamics of requests that are from the first to the third place:
