Accurately forecasting the performance of future digital campaigns is an important part of digital marketing. With PPC costs increasing and competition growing, and the advancement of AI, some businesses are starting to use tools to implement time series forecasting into their digital marketing planning. When used correctly, it can help stop overspending on Google, Meta and other key platforms and ultimately allow businesses to plan and allocate resources more efficiently.
What is Time Series Forecasting?
First things first, let’s explain what time series forecasting is. Time series forecasting is the process of analyzing historical data to predict future values. Unlike static data analysis, time series data is sequential and often influenced by patterns such as seasonality, trends, and cyclical behaviours.
Some of the key aspects of time series data include:
Trends: Long-term increases or decreases in the data.
Seasonality: Regular, repeating patterns, such as higher traffic on weekdays.
Sales and Events: Spikes or drops in activity linked to specific campaigns, promotions, or external events such as holidays.
Noise: Irregular fluctuations that are not explained by a trend or seasonality.
How can time series forecasting benefit a digital marketing strategy?
There are several ways in which time series forecasting can benefit agencies and brands when it comes to making better, data-driven decisions. These are:
Budget Optimization: The ability to predict future campaign performance to allocate budgets in a more efficient way.
Performance Benchmarks: Being able to produce realistic KPIs by understanding what’s happened in the past, using historical patterns.
Audience Targeting: Knowing peak engagement times to forecast and schedule ads for maximum impact.
What are the barriers to implementing time series forecasting into your digital marketing strategy?
If you ask most agencies or brands, they will probably say that at present, they do not have a sophisticated system for forecasting the future performance of digital marketing campaigns. One of the main barriers for implementing time series forecasting is the lack of technical expertise. Implementing and running forecasts often require significant time and data science skills. The cost requires significant investment in technology and tools (not to mention the cost of a data science team) so may not be feasible for all.
Another challenge is the fragmentation of data. Many businesses have their 1st-party and 3rd-party data spread across different platforms or systems, making it difficult to centralize and use the data for accurate forecasting. Without consolidating all relevant data into one place, the insights from time series forecasting can be less reliable, or worse, inaccurate
Additionally, time series forecasting often requires high-quality, consistent data. Missing data or inaccuracies can significantly affect the reliability of predictions.
How to integrate time series forecasting into your digital marketing strategy
Understand your metrics and your goals.
Define what you want to forecast and why, including the metrics you want to measure your performance against. For example, ‘How many clicks can we expect on our ad campaigns next quarter?’ Or ‘How do we achieve 700% ROAS in our ad campaigns in the next month?’
ASK BOSCO® helps you easily set clear forecasting goals by integrating your data and providing real-time insights into performance. You can quickly ask the platform for a budget plan to get future predictions and tailored forecasts for your specific marketing objectives.
Consolidate and prepare your data
Collect and consolidate all your historical data relevant to your target metric, such as website visits, ad impressions, or conversion rates. Ensure the data is clean, complete, and consistent.
With ASK BOSCO®, you can consolidate your data from over 400 sources into one place, ensuring that you have accurate and comprehensive data without the hassle of managing multiple platforms. This eliminates manual error, data fragmentation and ensures your forecasts are based on high-quality, unified data.
Choose a Model
If you have an in-house data science team, the choices for implementing a time series forecasting model include:
ARIMA (AutoRegressive Integrated Moving Average)
Pro: Effective for data with clear trends.
Con: Struggles with data that has strong seasonality or irregular patterns.
Exponential Smoothing (ETS)
Pro: Good for handling trend and seasonality.
Con: Assumes future patterns will closely resemble past behaviour, limiting its flexibility in dynamic environments.
Prophet
Pro: Designed to handle strong seasonal effects and holidays.
Con: While optimized for Facebook-type data, it is flexible enough to work on a variety of business datasets, though it may not capture complex patterns as well as other methods in some cases.
Machine Learning Models (e.g., LSTM)
Pro: Good at capturing complex, non-linear patterns.
Con: Requires large datasets and significant computational resources, along with significant data science expertise for tuning.
ASK BOSCO® streamlines forecasting using AI-powered statistical modelling, with features developed and continuously refined by our in-house data scientists. This means that the most suitable model will always be applied to your data, without you needing deep data science skills. By integrating time series forecasting for daily pacing and our own custom algorithm to calculate expected costs and outcomes for monthly forecasts, ASK BOSCO® provides you with actionable insights to optimize your budget allocation and drive better performance across all your campaigns. Saving time, optimizing budgets and eliminating guesswork.
Act upon the model’s forecasts and use human intervention too
Once your model or platform has provided you with a plan or forecast, you may wish to create multiple forecasts based on various scenarios. For example, you could simulate different budget allocations or test varying targeting strategies or swap metrics. This approach enables you to assess potential outcomes and make more informed decisions, ensuring your marketing strategy remains flexible and resilient.
The forecast you create can then inform your marketing strategy, but remember that while statistical models are powerful, human intuition and expertise are also invaluable to add to the work that the model has predicted.
ASK BOSCO® makes it easy to turn your forecasts into actionable insights. You can set budget recommendations, allocate resources efficiently, scenario-plan based on different criteria, and adjust campaign strategies based on predicted trends, ensuring your marketing efforts are proactive and data-driven.
What does the future hold for Time Series Forecasting
As time series forecasting continues to evolve, there are several key trends and advances that will shape its future in digital marketing. The integration of cutting-edge technologies will further enhance forecasting capabilities, making it more accessible and impactful for marketers. Here are some of the exciting developments to watch:
Automated Machine Learning (AutoML)
Platforms such as ASK BOSCO®, H2O.ai and AWS Forecast are simplifying the modelling process, making it easier to build and deploy forecasting models without requiring extensive data science expertise. This democratization of machine learning is helping businesses harness the power of data without a large investment of in-house data science teams.
Real-Time Forecasting
With the rise of streaming data, marketers will be able to adjust as needed, ensuring that campaigns stay optimized in real-time. This capability will allow for more dynamic decision-making and immediate responses to changing conditions, providing a more agile approach to digital marketing.
Causal Impact Analysis
This approach helps marketers understand how specific actions, such as a price change or campaign tweaks, affect trends and outcomes. By isolating the impact of these actions, businesses can make more informed decisions and drive more effective strategies.
ASK BOSCO® is at the forefront of these innovations, offering an AI-powered platform that integrates advanced forecasting techniques into your digital marketing efforts. The platform ensures that your forecasting is not just accurate but also actionable, empowering your team to stay ahead of the competition.
If you’d like to find out more about, ASK BOSCO® and its forecasting and media planning capabilities, please contact our team. You can also view this blog to understand more about how the Budget Planner feature within ASK BOSCO® works.
