Client's Data

Client's Data
The client approached with a website and the desire to set up contextual advertising. At that time, they already had some contextual advertising running with some results. During our analysis, we identified mistakes and realized that the campaign had been set up in an amateur way. Firstly, the keywords were inconsistent and lacked any logic. One campaign contained all the keywords and only one ad. As a result of the launch, the client claimed to have received 4 potential leads, but we couldn’t see this in the campaign because the campaign didn’t have lead generation enabled, and there was no synchronization with analytics or conversion settings.
Problem
Contextual advertising setup
Progress
Therefore, it was proposed to reconfigure the contextual advertising campaign. After gathering the keywords, we identified 14 main search campaign groups for the client that needed to be set up. The campaigns were divided by geography, type, topic, target, and untargeted (informational and conversion). There were a total of 14 campaigns. We set up phrase match and launched the campaign. As a result, on the first day, we received 1 lead and spent 9 UAH.
Since the client was from Kryvyi Rih, where the demand was not particularly high, on the second day after launch, the lead cost was 9 UAH. We realized that something was wrong, and Facebook didn’t like that we had launched a phrase match campaign. I switched it to broad match and added more negative keywords, but the performance was still poor. It was decided to make one campaign with broad match and add a huge number of negative phrases with non-target keywords of various types. During the launch process, we didn’t transfer the goals.
The client’s website didn’t have a thank-you page, and unfortunately, we couldn’t influence the correct coding. As a result, it wasn’t working, so it was suggested to create a thank-you page and embed the conversion code from Google Ads there. This gives faster conversions and, thus, makes it easier to control the campaign’s performance than through Google Analytics.
After launching, we immediately got the first results, the leads came in well, and we got 2 leads, spending up to 200 UAH. The cost per lead was about 90 UAH.

After assessing the quality of these leads, it turned out that a few of them had already made an advance payment and became clients, so we continued the cooperation. Our goal was to outperform all competitor bids, be on top, and get a lot of clicks. We scaled the campaign and increased the daily budget, but the number of leads was zero on the first day. The client’s goal was to receive 4 clients per day, i.e., 100 potential clients per month. After scaling the campaign, we stopped getting leads altogether, although when we checked the forms, website, and ads, everything seemed fine. It turned out that during the holiday season, seasonality is very important, and sometimes there are days when people show interest in an event but do not submit applications. This process is very hard to control with contextual advertising. To get more leads, we needed to attract other traffic sources, such as Facebook and Instagram, which we did. When the client came to us, the cost of one lead was about 90 UAH, and they received 4 leads, spending about 400 UAH. When we checked, we saw that the cost per lead had increased to 156 UAH. The price is now about 120 UAH since there were no conversions at the beginning.

Final Result
The advertising campaign showed which keywords were bringing the client. If the client had no goal of increasing the volume of leads, the cost per lead could have been reduced to 60 UAH and optimized. With this campaign, where 70 keywords are already working, including only these keywords would have saved the client money. Now, the main task is scaling the advertising campaign and identifying new keywords, so it is too early to optimize. Using all possible methods we employ, we check the keywords and add to the negative keyword list those search terms that are triggered by untargeted queries.
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Reviews
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