Foresight is one of the most valuable resources any marketer can have. Understanding consumer needs, and delivering on them before your competitors, is a surefire path to business success. That’s why industry leaders use trend forecasting and trend prediction to make some of their riskiest but most crucial business decisions.
If you need a better understanding of what trend forecasting is and how it’s done, you’re in the right place! Read on for a detailed rundown of trend forecasting for marketing, PR, and other communications professionals:
What is trend forecasting?
What is trend projection forecasting?
What is trend analysis forecasting?
What are trend forecasting methods?
Trend forecasting examples
Trend forecasting tips
The final takeaway on trend forecasting
What is trend forecasting?
Trend forecasting is the practice of making educated predictions about how trends will change and develop over time.
Usually, the end goal of trend forecasting is to produce models and projections for how a trend will progress. Marketers use trend forecasting to create strategies that anticipate consumer needs and reduce risk for brands and organizations.
Trend prediction vs trend forecasting
Trend prediction and trend forecasting are, in many cases, used interchangeably. That’s because both use data, research, and other information to draw conclusions about changes in industry, market, and consumer patterns.
In some contexts, though, there is a subtle distinction between the two that can be useful for planning outcomes for market research, audience intelligence, and other analyses. In these cases, trend prediction uses that process to determine what new pattern shifts will emerge, while trend forecasting uses it to determine how already-identified pattern shifts will play out.
Find a more detailed explanation of what trends are and how to find them in our trend detection guide and learn more about trendspotting.
Short-term vs. long-term trend forecasting
Trend forecasting often falls into one of these two time-related categories:
- Short-term trend forecasting, which aims to understand how trends, especially micro-trends, will progress in the immediate future. This kind of forecasting looks ahead to the next month, quarter, season, or couple of years.
- Long-term trend forecasting, which projects how trends, especially macro-trends, will progress over years, decades, or longer.
In general, long-term forecasting requires data sets that include longer time periods than short-term forecasting.
What is trend projection forecasting?
Trend projection forecasting is a subset of trend forecasting that uses historical data and patterns to hypothesize and/or model how trends will develop in the long-term or short-term future.
What is trend analysis forecasting?
Trend analysis forecasting is a subset of trend forecasting that, like trend projection forecasting, uses historical data and patterns to determine how a trend will play out.
Trend analysis forecasting can also include what is known as qualitative forecasting, which hypothesizes and/or models how trends will develop based on analyses of their origins, drivers, context, and other forces. This form of trend forecasting can involve a wider range of research, data sets, and advanced tools than trend projection forecasting alone.
What are trend forecasting methods?
The specific steps you take to forecast trends will depend entirely on your needs, objectives, business environment, and more. In general, though, they will fall within these categories of trend forecasting methods:
Judgmental forecasting
As the name implies, this method involves judgment based on past patterns. This can often involve lots of observation and experience, combined with research, to create broad predictions. This method is done formally or informally and can be the only option when hard data isn’t available. However, it is also much more susceptible to human error and bias.
Qualitative forecasting
Qualitative forecasting relies on careful collection and analysis of information from a wide range of sources that could include everything from consumer opinion data to history books. Analysts then use that information and their expertise to predict how a trend will progress.
This method involves a lot of time and careful searching for patterns and uniting themes, making it best suited for subject matter experts. However, it can be the best option for situations where impacting forces are varied and creativity is needed.
Statistical forecasting
Statistical forecasting relies on large data sets (big data) and complicated, computer-assisted analysis to predict the future course of a trend. Data analysts use this method of trend forecasting to create statistical models that are highly precise. This method is often faster and, in many cases, more accurate and objective than judgemental forecasting, but without the right data, it can also miss important context.
Advanced solutions like our social listening and analytics platform use sentiment analysis, image recognition, and other features to mitigate those kinds of oversights for marketers.
Many cases of trend forecasting call for a blend of qualitative and statistical methods to get the certainty of statistical calculations with the real-world knowledge of a human expert. This is where the necessity of powerful tools comes into play.
With the right solutions, data-driven marketers forecasting at any level can make trend projections that are holistic, informed, and accurate.
Trend forecasting examples
Now that we’ve covered some of the ins and outs of trend forecasting, let’s see what it looks like in practice.
- Trend forecasting in technology: In 1965, Intel co-founder Gordon Moore correctly forecasted that as computers became more powerful, they would also become less expensive and more accessible to the average consumer.
- Trend forecasting in fashion: In 2015, a fashion trend forecaster used the media database IMDB to project how forthcoming sci-fi films would influence the popularity of space-inspired patterns and designs.
- Trend forecasting in sports: Betting experts used historical player data and statistical models to correctly predict the winners of almost every stage of the 2019 Professional Golf Association Tour.
- Trend forecasting in beauty: Leading beauty company Shiseido uses Meltwater’s social listening and analytics platform to forecast trends in marketing communications preferences for different audiences segmented according to their shared interests.
Get an inside look at one trend forecaster’s process in our guide to trend spotting and forecasting for PR.
Trend forecasting tips
With the right tools, trend forecasting is doable at any scale, but there are a few things you can do to get an advantage over your biggest competitors. Follow these tips to give your forecasting a boost.
- Monitor trade and industry journals.
These publications offer the level of context and expertise that can bring your trend forecasting program to the next level. While reading through these outlets as thoroughly as you can is ideal, the reality is that most of us are short on time. Use your media intelligence suite to track relevant topics across these publications and surface important clusters of topics and narratives as they emerge. - Pay attention to overlooked conversation leaders.
Listening to consumer opinions (via consumer intelligence) is a must, but marketers too often ignore the leaders who influence consumer opinions and behavior most directly. Targeted social listening can help you find and, most importantly, understand those leaders. For example, Pernod Ricard pays close attention to bartender opinions and preferences to predict cocktail trends and Haleon looks to dental hygienists for insight on how to connect with consumers of its dental health brands.
Read more about how Pernod Ricard and Haleon use Meltwater to forecast trends. - Check out indirect competitors.
What can athletic shoe brands learn from luxury shoe brands? What can beverage companies learn from cafes? And what can motorcycle dealers learn from cycling shops? A lot! Monitoring and benchmarking your brand against direct and indirect competitors can reveal new trends and trajectories by comprehensively centering consumers. - Consider non-textual information.
Visual objects, like pictures, gifs, and memes, are a huge part of online communication today. Analyses that include textual and visual elements will always be stronger than those that don’t. Advancements in AI technology, specifically AI-powered computer vision, have made visual analysis a must-have feature in any customer intelligence solution. For example, our platform leverages computer vision technology to detect and analyze logos, faces, scenes, objects, and other visual elements to zero in on emerging trends. - Keep a sense of perspective.
Trend forecasting reduces risk for businesses, but always remember that nothing is 100% certain. The COVID-19 pandemic’s start in 2020 is one obvious example of how unforeseen events can wipe out even the most well-thought-out projections and plans.
The final takeaway on trend forecasting
There you have it — a high-level summary of what trend forecasting is and how it’s done. There is much more to explore on this subject, but if there’s one point you should come away from this overview with, it is that trend forecasting is only as successful as the data and tools used for it allow.
For marketers and communications professionals, social listening and media monitoring solutions are trend forecasting must-haves. With the advanced features included in the Meltwater Suite, you can look into the future of your market with a click. To learn more about how you could use Meltwater to identify industry or consumer trends, fill out the form below.
