Advertising Tips for Black Friday and Cyber Monday Campaigns
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In 1971, Richard Nixon was president, All in the Family debuted on CBS, and the first Starbucks opened in Seattle. It’s also the year the Harvard Business Review featured a story on how to pick the right forecasting model for your business.
Much has changed in 49 years, but the relevance of forecasting models remains strong — particularly at a moment overcome with uncertainty. Though revenue forecasts, which predict business income over a fixed period, aren’t always fool-proof, they can help businesses anticipate challenges before it’s too late.
In fact, one of the most important aspects to remember about forecasts, as marketing software provider HubSpot reminds us, is perfection is not the goal. Instead, use forecasts to plan for your business and adjust as needed. Before you can tap into the power of forecasting models, you have to choose one. And with so many options, we’re diving into everything you should know.
When it comes to forecasting models, they boil down to two different methods: traditional statistical methods, such as regression analysis, and modern machine learning methods, like neural networks. The one you choose depends on who is responsible for forecasting within your organization and what that person’s background is. Someone with experience in data science may opt for machine learning, while business professionals are more likely to rely on statistical methods.
To identify the best fit for your company, engage employees in a conversation before you make your final decision, according to the global consulting firm Bain.
Here’s an inside look at the most common models:
These basic forecasting models are the tip of the iceberg. In terms of more sales-specific methods, you can also consider:
The one aspect these models have in common is data. No matter which method you choose, remember it’s only as good as your data. Therefore, it’s essential to get buy-in from your sales team, be in regular communication, and hold staffers accountable, so the data they input into your CRM platform is accurate and actionable.
For more on why data-driven marketing is crucial:
This is once again where 2020 is an exception. Because we’re in the midst of an incredibly challenging time to plan for anything, it may be tempting to think forecasting models are useless. However, the pandemic has made forecasting more important than ever as it gives business leaders a roadmap to chart the course during this unprecedented time.
If you’ve looked around and realized your existing forecasting tools are inadequate, this may be a smart time to reevaluate what you’re using to find the best fit for your brand. Though no one likely accounted for the COVID-19 pandemic in their 2020 forecasts, it’s crucial businesses re-assess their projections for the year as soon as possible. This will give key stakeholders the best insights to figure out the way forward.
It’s best to use machine learning models in this endeavor, according to KPMG, a professional services network. It also suggests ultimately automating the forecasting process, so you’re ready with the most advanced tools available before the next crisis. Also, remember that to update your 2020 forecasts, you’ll need to pull external data related to the pandemic, such as how governments respond and the potential impact on consumer demand.
Unfortunately, forecasting models are not crystal balls. They don’t show us the future as it will be — and they definitely didn’t foresee a global pandemic. But they’re the closest tool we have to a clearer picture of what the future may hold.
While the options may seem endless — and they are to an extent — this only underscores the importance of searching for the right partners, which will help you find the right forecasting model, tap into its power, and drive your business forward.
For predictions on post-pandemic trends to watch out for:
Last updated on August 16th, 2022.