Case on contextual advertising for air conditioners

Goals set by the client:

- increase the number of target visitors to the website;
- increase the number of inquiries and calls;
- reduce the cost per click.

Work plan:

1. By analyzing the client's website, target audience, and studying competitors, it was decided to expand the list of key queries.
2. 3 to 5 ads were written for each key phrase, using ChatGPT.
3. All key phrases were grouped into categories: "by relevance" for more convenient budget management and cost optimization.
4. AI found new keywords that fit.
5. To exclude non-target transitions through ads, we expanded the list of negative keywords and continue to add to it.
6. Implemented negative keyword cross-matching to avoid ad competition in one campaign.
7. Added targeted ads to similar audiences to increase conversions.

As a result of implementing this strategy, the following indicators were achieved:

Bounce rate: 12.67%
Page depth: 2.63 pages
Time on site: 1:32
Clicks: 1572
CTR: 13.71%
Average cost per click: 8 UAH.

For this topic, advertising is suitable both in search and in the contextual-media network.

* The complexity lies only in finding a profitable source of clients. That is, if you use the contextual-media network more, it is worth "getting involved" with audiences and topics, with articles and age, as they had the main return. And in the case of the search network, a strict selection of keywords is required.

What are the results?

Inquiries: 107
Average inquiry price: 300 UAH.
Website conversion rate: 6.8%.
Advertising expenses: 32,100 UAH.

Plans for the next month:
! Our account has already learned well and understands its target audience, which is very important.
1. Plans for this month include launching Performance Max and Smart campaigns and checking the conversion rate.
2. Launch an ad video to our audience who has already visited the site but did not submit an inquiry.