Data & strategy
Data-driven forecasting: what is it?
When you set goals, you want to do so as effectively as possible: you want to aim high while remaining realistic at the same time. By working with data instead of relying solely on intuition, you ensure that your objectives are both strong and achievable.
What is a data-driven forecast?
A data-driven forecast is a means (not an end!) that you use to make predictions about future events by analysing past data. Particularly in the online landscape, making data-based predictions offers valuable opportunities. A data-based forecast:
- Provides more specific objectives. By analysing different data sources that are relevant to your objective, you not only gain a broad overview of all the possibilities, but also a clear understanding of where the opportunities lie for specific areas;
- Provides insight into the processes that lead to success, allowing you to organise the practical approach even more effectively and increasing the likelihood that the objectives will be achieved;
- Provides a better picture of the expected results. Because you have analysed the current path thoroughly and therefore know which success factors are important, you can determine future expectations more accurately.
By actively working with data, you can identify trends, align your strategy with them and improve decision-making. In addition, by monitoring the data periodically, you can make timely adjustments when something is not performing as desired.
Because you have defined in advance what you are looking at as a company, you also speak the same language internally and can adjust the strategy more quickly in areas where the results are falling short. Adjusting the work accordingly becomes much easier and more efficient. More than enough benefits, then, but how do you put such a forecast into practice?
How do you make a data-driven prediction?
A data-driven forecast starts with the question: what do you want to achieve? Let us take a concrete example: the growth of organic visitors from the search engine and the higher profitability resulting from this traffic.
Based purely on intuition, you might set the goal of seeing 30% growth in organic sessions from the search engine in the same month next year, and an increase of 20% in profitability (profit margin minus SEO costs). Well phrased, but what are the figures based on? It is much better to look at past data and use it to determine a well-founded objective.
When you want to create a data-driven forecast, you first identify which data is important to use. You determine this by mapping out which factors are responsible for your success and which sources can measure these factors for you. In the online landscape, for example, consider sources such as Google Analytics and Google Search Console. Once you know which data sources you need, you can map out that data.
To understand where you currently stand, it is sensible to compare the current situation with, for example, the same period last year, so that you can see how the trend is developing. You can then use this trend development to make meaningful predictions about the future.
Taking stock of the data
Returning to our example objective of organic traffic, you could look at the following data for your data-driven forecast:
Determining what your forecast will be
By bringing the data together, you now have an overview and can analyse the data to arrive at your objective. To do this, you look at the trend development and determine which elements are responsible for the current growth trend.
In the example of growth in organic traffic and profitability, these elements are an improved position accompanied by a higher CTR. When you keep the SEO budget and approach the same, you use the competitor analysis to estimate the expected change. Based on this data, you might expect to move up by an average of at least 1,2 positions. Based on Google Search Console data, you can estimate the new CTR. You can then use this to calculate how many clicks/visitors this represents.
You can then ask yourself whether you consider the growth from this data-driven prediction sufficient, or whether adjustments can be made within the current approach to achieve even stronger growth. For example, investigate how much of an additional boost could be achieved by shifting the focus from blogs to optimising category pages, product pages with a relatively high margin or authority building. Is additional budget perhaps needed to achieve higher profitability, and if so, where should that budget be allocated?
By changing the focus and SEO activities, you achieve greater returns thanks to the expected position growth for search terms with higher search volume. In our example, this results in a new objective for organic sessionsBy placing even more focus on category pages and products with a relatively high margin, you can then expect this to also lead to higher revenue. The objective ultimately comes down to SEO profitability growth of 15%.
Data-driven forecasts summarised
- Determine what you want to predict;
- Determine which underlying factors play a role and what the end result is;
- Select the sources that track the development of these factors and the end result;
- Determine what you want to compare and over which period;
- Analyse the data and determine the trend;
- State the forecast if the current situation continues;
- Consider which factors you can influence and what conditions apply if you want to improve the forecast;
- Formulate your forecast and conditions based on your analysis.
Good luck!
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