Methodology
While positioning the brand’s marketing strategies, we used Google Display Network ads as well as search ads. We needed a channel where we could collect the data of potential customers to get their information on the website. We thought about a benefit we can offer to potential customers online and created an online level test where consumers can measure their English level. Thanks to the call to action buttons that we have placed in many places on the website, we have made the user able to measure his English level by taking a level test where he can measure his knowledge directly. As a result of all our advertising expenditures, we made landing page optimization continuous and created a better conversion funnel. For our multi-device marketing strategies, we made separate optimizations for mobile and desktop for computer.
We had to complete this exam page with the right marketing setup. In other words, the message that the consumer sees in the advertisement and the experience he encounters on the website should complement each other. In our advertisements, we chose a visual that could be the first question of the placement exam. In our GDN (Google Display Network) ads, with his message “I learn English at Conversation Club. I ….. a student.” and the “Answer: Answer the Question” call-to-action button, the user could directly access the page where he could start the exam.
We have done A / B testing on target audiences using many types of targeting. In order to reach deep target audiences, we created users with different specifications. Using the Analytics audience targeting feature, we created different audiences according to the commitments made within the site. For example, we showed ads to different audiences such as those who started the exam but left without completing the exam, those who came to the homepage from pull marketing such as Google search network or organic, and did not start the exam, Google remarketing audiences (smart list), audience within the market: “Foreign Language Study”.
Simultaneously, we made traceable impact optimization in the campaigns. We enabled machine learning algorithms to learn better by selecting leads in campaign targets.
Innovation
In order to obtain the information of potential customers with these advertisements, we obtained information such as e-mail address and mobile phone before the exam. Each potential customer is called one by one by the speaking club sales team, along with the online level test score they have received, and the questions that potential customers are curious about; answered by phone, email or face-to-face methods. However, in all these steps, there was another problem we had to solve: Although some of the potential customers shared their knowledge in the online practice test, some of them were not so interested in the training. To solve this problem, we used the value track feature of Google AdWords.
Thanks to the value track feature, we used a very detailed tracking template in the domain name where AdWords ads are placed.
{lpurl}?campaignid={campaignid}&adgroupid={adgroupid}&targetid={targetid}&network={network}&device={device}&devicemodel={devicemodel}&placement={placement}&target={target}
Thanks to this tracking template, we have enabled AdWords to automatically reflect information such as in which domain name (domain) the ads are displayed, on which device type, on which networks our ads are shown, to the final URL. As a result of our work with our customer’s IT (IT) team, we enabled them to save the information in the tracking template while recording the leads from the advertisements in the database. In this way, we started to optimize not only cost per action (CPA) but also cost per qualified lead. This had a very positive impact on sales. Now, with the brand, we can obtain nearly twice as much quality leads for a quarter of the price. This allows our customers to increase their sales and constantly their budgets for digital marketing.
In order to measure the performance of the campaign, we prepared a data studio report that our customers can easily understand. By explaining the logic of the campaigns set up to our customers, we explained the conversion-enhancing features of AdWords such as custom affinity audience, in market audience, value track, machine learning, bidding strategies. Our customer also supported us by understanding the logic of all these attempts and being patient enough to achieve success.
We used a “location-based” attribute model instead of the last click model to measure your ads. Because the conversion time was not very long, and in order to understand the advertiser’s budget in the most effective way, we had to understand the sources that brought the first click and the last click in the conversion process. In this way, we have established a mechanism that rewards not only the campaign that brought the last click, but also the first conversion source and the last conversion source in terms of its contribution to the total conversion.
We also designed non-Google (non-google) campaigns for our multi-channel marketing (Omni-channel marketing) setups, and we followed the Instagram Story ads with a good UTM URL structure and optimized the campaigns through Analytics data. In addition, we retargeted the new visiting customers we brought from these sources on Google Display Network and did a 360-degree marketing.
About
konusmakulubu.net
Konuşma Kulübü is basically a language school for those who want to speak English. It is a platform specially designed for those who want to speak English in daily life and differentiated according to the exchange rates of the participants. It aims to teach English to end-users with native speakers of English on subjects that are completely adapted to daily life. Founded in 2015, the brand grows nearly 100% every year with the power of internet and internet advertisements. Today, the Speaking Club has become a growing business by making agreements with many of Turkey’s leading universities and adapting this business model to many universities.