6 steps to AI-driven budgeting and forecasting for digital marketing

6 steps to AI-driven budgeting and forecasting for digital marketing

Gather historical revenue and conversion data from Google Analytics across all channels. 

Collect spend data for all channels.

Calculate ROI for each channel. 

Data and infrastructure

All data should be available in a centralized storage such as a data lake.

It is easier to access clean and centralized data for training the model.

Install required python libraries such as pandas, numpy or scipy.

Perform exploratory data analysis to identify trends and seasonal patterns by running python libraries and statistical analysis  

Forecasting and budgeting

Use forecasting models such as SARIMA to forecast the revenue from each channel based on the spend. The model will account for seasonality trends in the data

Use statistical optimization techniques to find the best budget allocation across channels.

Working model output 

Current average spend across the top channels:

After executing all the steps given above, here’s the recommended allocation by the budgeting model:

Individual channel allocation

Once you have the budget allocation for each channel, the next step is to break it down further and identify specific sources or platforms within each channel. 

For example:

Within the organic search channel, you might consider sources like Google Business. 

For paid search, platforms like Google Ads and Facebook. 

This helps determine the precise budget needed for each source.

For our use case, focus on the organic search channel. Run the budgeting model for all sources within this channel to determine each source’s allocation.

After executing all the steps, here’s the recommended budget allocation for organic search sources:

Strategies and solutions to maximize the full-funnel digital experience 

Now based on the recommended allocation, deploy the strategies to optimize GBP Listings and Google Search.

AI in digital marketing: Smarter budgeting and forecasting

In the AI era, budgeting and forecasting can be done in real time if data from various customer touchpoints and channels is centralized and readily available throughout the customer journey. 

By leveraging AI, you can optimize marketing performance by allocating the right budget to each channel based on its contribution to achieving your business goals.

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