Promotion of the credit broker site

Semantics

The semantics of this site is, on the one hand, quite simple, and on the other hand, there is simply a huge amount of it, and manually collecting such a large amount of semantics at once is a rather time-consuming process. That is why the widest possible semantics was collected for marker queries, and then monthly clusters were separated from more frequent to less frequent. Further, point and detailed semantics were collected on them. What is interesting, when collecting semantics, it was important to take into account the fact that it is necessary to collect all the maximum “tails”, because they brought traffic at the beginning, while the mid and high keys needed time to get to the TOP.

That is, the tactics of initial traffic were used at the expense of medium-range keys with low competition for initial traffic, and then these keys in a pile with good optimization and a strong referral profile pushed more competitive and frequency keys to the TOP.

Content

For a good ranking of pages in terms of queries, not only texts containing keywords were important, but also blocks on pages and structural elements that helped to improve user experience and interaction with the page. Blocks with credit terms, tabular blocks with comparison, etc. All this had to be taken into account when creating content.

Blocks for quick decision-making and various forms of customer data collection for further work with them were also important.

In order to write the right SEO content, competitors’ texts were analyzed, their structure, the occurrence of keywords and the structure and formula of the “ideal text” for the niche were formed. In fact, most of the texts were written roughly according to a similar structure

After the basic optimization of the site, the content on the pages was constantly updated and added due to the update of offers, microcredit organizations, and so on.

Expanding the structure

To expand the structure, two main points of the collection of semantics were used. Since this site is an aggregator of various organizations, the semantics had to be ambiguous. The first group of clusters are general requests such as “money for…”, “loan from UAH 1,000”, “loan without reference”, etc. And another group used brand requests from organizations so that the first point of contact was with our site. Since many organizations had weak websites, we were able to outperform our competitors on many brand keys.

Therefore, groups of pages were divided into keys by purpose and keys with brands.

Referral profile

After analyzing the links of the site and performing a similar task with the top competitors, we calculated the average ratio of anchor/non-anchor, article and crowd, follow and nofollow, formed a strategy for the set of link mass of the site based on the analysis and calculated the budget.

For this niche, not only outreach links are necessary. The “interest” is the presence of a large number of natural links. This is due to a large number of publications on thematic forums. Therefore, in this case, most of the links were just from forums, and anchor article links were created only for the most frequent and “bold keys”. We pay special attention to the selection of the highest quality donor domains.