Proud partner
Case
Social
Predictive modelling as a factor in determining SEO focus
InShared
Online non-life insurer
Clients such as InShared are such a good fit for our agency because, as a fully digital insurer, they are always looking for innovative ways to optimise their operations. It’s a mindset we, as a forward-thinking agency, absolutely love. Given how competitive the insurance sector is, the next challenge focused on innovating the SEO strategy. To tackle this challenge, we developed a unique approach. We linked various predictive models together to better map out the SEO strategy. Let this success story surprise you!
The golden combination of tooling
If you rank Traffic Today ’s marketing tools by relevance, you’ll find tooling high up in the list. In the case of InShared, data from Semrush, Google Ads and Google Analytics formed the main sources. Using these variables, our SEO marketer Jeroen Snel developed a dynamic predictive model in Google Sheets, which displays keyword-related revenue forecasts. “The model analyses various variables, such as search volume, competition level, cost per click (CPC) and current rankings. This is necessary to make an accurate forecast of the potential revenue for each keyword. It makes our work much more measurable, something we consider very important at Traffic Today,” says Jeroen Snel.
The model is designed to be dynamic and user-friendly. Up-to-date data from Semrush and Google Ads is added to the designated sheets, ensuring the model is automatically updated. The model also recalculates all relevant metrics as soon as a new keyword or target position is added, which further underlines the model’s relevance.
One of the key advantages of this approach is that the model can be easily adapted and updated by any marketer. This eliminates the need for expensive software or specialist training.
Making an impact with forecasting
Search volumes – and therefore supply and demand – are subject to change. After all, fewer people will be searching for winter sports insurance in June than when ice crystals are visible on car windows. This is one of the reasons why InShared asked us to help devise a model that can anticipate this.
The model we have developed uses conversion data from Google Ads, which calculates how much traffic is needed to achieve an X number of conversions. The average CPC calculates the cost of SEO, as if it were paid traffic.
The result? Potential savings by using SEO instead of paid advertising!
Grow faster by working smarter
The implementation of this predictive model has delivered fantastic results for InShared. It has enabled us to optimise our SEO efforts and deploy our resources more effectively. With this model, we were able to focus on the keywords with the greatest potential for conversion, which led more quickly to the desired result.
In addition, the model has also helped us to quantify the financial impact of our SEO efforts. By treating SEO traffic as paid traffic, we were able to identify savings. These have led to the optimisation of our own SEO strategy. A huge victory for InShared!
Evaluation of results
With a large number of campaigns and hundreds of videos, it’s absolutely vital to keep a close eye on everything and check in regularly. That’s why we use handy dashboards for each product line, which clearly display all key data and results. This way, we know exactly what’s going on and can make quick adjustments if necessary.
Although we focus primarily on generating registrations for open days, we also take into account the subsequent stages of the customer journey.
By strategically utilising online advertising, we have laid a solid foundation for attracting more student registrations. We aim to reach the target audience – consisting of prospective students and their parents – at the right moments and through the right channels. We do this throughout the entire customer journey, from the initial introduction to the final registration.
Replicability of a proven model
This predictive model has proven to be a valuable tool for InShared. Not only has it helped to improve our SEO efforts for this client, but the model has also demonstrated that it can be of value to partners operating in other markets.
The dynamic nature of the model – which allows up-to-date data from Semrush and Google Ads to be fed in, with the model automatically adapting – makes it a powerful and flexible tool that should be considered for every type of client.
In the future, we will continue to refine this predictive model further, so that we can manage InShared’s marketing budget even more efficiently!
Want to grow together?
Curious to find out how we can help your business grow with targeted online marketing campaigns? Do you want to generate more leads and increase your brand awareness? Our experienced team is ready to help you!