Webinar: Mastering Sales Forecasting with Predictive AI: From Guesswork to Science
Accurately forecasting revenue is crucial for making informed decisions and planning for the future, but it can be challenging for sales and operations teams. It’s traditionally been a complex, manual, and biased process that takes a lot of guesswork and repetition—and a few missteps in understanding market signals, dependencies, and noise can turn plans upside down.
What we covered:
- The basics of time series modeling for analyst and operations teams and how it can be used to forecast revenue.
- The common challenges that arise when predicting sales revenue and practical tips for overcoming them.
- Best practices for cleaning, preparing, and exploring your data to improve forecasting accuracy, including how to identify key drivers and use them to make more informed predictions.
- How to share your insights and models with your team and apply them to make informed data-driven decisions.
Chapters:
0:00 - Introduction
2:25 - How to use ML for forecasting
5:22 - Overview of Akkio
10:15 - Start forecasting in Akkio
11:40 - Ignore values in time series
14:04 - Choosing the forecasting model
15:46 - Training the ML model
16:36 - Insights report
22:00 - Sales forecasting for liquor sales in Iowa
32:10 - Q&A
Learn more about Akkio:
➡️ Twitter: https://twitter.com/AkkioHQ
➡️ LinkedIn: https://www.linkedin.com/company/akkio
➡️ Website: https://www.akkio.com/
➡️ Newsletter: https://ai-mavericks.beehiiv.com/
Thanks for watching!
-The Akkio Team
Accurately forecasting revenue is crucial for making informed decisions and planning for the future, but it can be challenging for sales and operations teams. It’s traditionally been a complex, manual, and biased process that takes a lot of guesswork and repetition—and a few missteps in understanding market signals, dependencies, and noise can turn plans upside down.
What we covered:
– The basics of time series modeling for analyst and operations teams and how it can be used to forecast revenue.
– The common challenges that arise when predicting sales revenue and practical tips for overcoming them.
– Best practices for cleaning, preparing, and exploring your data to improve forecasting accuracy, including how to identify key drivers and use them to make more informed predictions.
– How to share your insights and models with your team and apply them to make informed data-driven decisions.
Chapters:
0:00 – Introduction
2:25 – How to use ML for forecasting
5:22 – Overview of Akkio
10:15 – Start forecasting in Akkio
11:40 – Ignore values in time series
14:04 – Choosing the forecasting model
15:46 – Training the ML model
16:36 – Insights report
22:00 – Sales forecasting for liquor sales in Iowa
32:10 – Q&A
Learn more about Akkio:
➡️ Twitter: https://twitter.com/AkkioHQ
➡️ LinkedIn: https://www.linkedin.com/company/akkio
➡️ Website: https://www.akkio.com/
➡️ Newsletter: https://ai-mavericks.beehiiv.com/
Thanks for watching!
-The Akkio Team
