These days, it’s a crime for a food business not to adopt advanced analytics. Read on to discover how data analytics is transforming the F&B industry.
10 Ways Data Analytics Is Reshaping F&B Businesses
The numbers don’t lie, but they can be confusing if they are just plopped in front of you to make heads or tails of them. You don’t need the data, you need the data to be analyzed, reported and presented in a digestible, understandable way. You need insights!
Thanks to modern technology, we can now count and track practically everything that matters in business that was previously unattainable. However, being able to collect big data is one thing; analyzing it is another.
If you run a food establishment, it’s already a sin not to adopt data analytics. After all, raw numbers aren’t going to crunch themselves. You need a powerful, intuitive platform to glean meaningful, actionable insights from your newfound figures, giving you the intelligence to manage your operations more effectively.
Are you on the fence about investing in data analytics? Here, you’ll learn how it’s been transforming fast food chains, bistros, clubs, sports bars, burger joints, coffee shops, bakeries, pizza parlors, cloud kitchens, and other data-driven players in the food and beverage (F&B) industry.
1. Enhancing Menu Contents
Generally, it’s easy to separate the dishes that sell more from those that don’t. What’s hard is understanding why some food items aren’t as popular or profitable as others. Chalking it up to something without concrete proof is futile at best and costly at worst.
Data analytics holds the key to understanding and engineering your menu.
Analytics has minimized the need for guesswork in menu creation. Historical data can reveal every menu item’s pricing sweet spot, identify appealing food pairings, highlight the favorites of different demographics, and underscore seasonal best-sellers.
By trial and error, you can enhance your menu over time without the use of sophisticated software. But data analytics shortens this process by allowing you to quickly learn the lessons your numbers are teaching you—which has a more immediate impact on your bottom line.
2. Identifying Operational Inefficiencies
Operational inefficiencies inflate your overhead. Everybody knows this, but the problem is that it can be difficult to determine which aspects of your operations could use some improvement.
Having data analytics capability can reveal patterns of operational inefficiency in large batches of raw data. This way, you can formulate strategies to optimize your staff, prepare and cook foods, serve customers, handle orders, or perfect any activity crucial in running your place smoothly.
3. Maximizing Inventory
Inventory mismanagement increases the risk of inaccurate forecasting, overproduction, spoilage, loss of stock, theft, and decreased food quality. With countless goods coming in and out of your establishment on a regular basis, staying on top of everything is a Herculean task.
It’s imperative to be numbers-driven and equipped with the right tools to get a handle on inventory management.
By using analytics to give your real-time and accurate information, you can improve your stock monitoring and rotation (especially when perishable goods are involved) and track product life cycles more closely. Ultimately, you can avoid getting stuck with unsellable, obsolete inventory.
4. Refining the Food Value Chain
A food value chain is only as strong as its weakest link. It can suffer from low-quality ingredients, unreliable suppliers, slapdash cooking, rude servers, or bad packaging.
Considering how long and complex food value chains usually are, it can be tricky to identify which components need fixing in order to consistently exceed customer expectations.
A cloud-based data analytics solution will help you see all of the cogs in the machine in one view. A customizable dashboard improves information visibility. Detailed, error-free reports render the intricacies of your food business are simple. Seamless integration makes it painless to pull and push data to supplement in-depth analysis.
With high-level managerial insight, you can distinguish the “rusty links” on your food value chain in a timely manner and address such liabilities quickly.
5. Predicting Future Demand
In business, history tends to repeat itself more frequently than you think. If you don’t learn the lesson from past events, you’ll be doomed to commit the same mistakes or fail to replicate effective strategies.
The use of predictive analytics can help you prepare for increased or decreased future demand and create smarter targets accordingly.
With access to predictive forecasting, you can quickly see how your sales are trending by outlet, and if you are on track to make your monthly sales budgets. What’s more, is as you gain more data, the predictions will just get smarter overtime, making your job easier month by month.
6. Demystifying Customer Behavior
Big data is the hallmark of e-commerce. If you generate some of your revenue directly through digital channels, you should map the customer journey as accurately as possible.
Advanced analytics will help you connect the dots and make sense of why your leads behave the way they do. Those that buy are just as interesting as those that bounce or abandon their cart, for behaviors are indicative of the marketing methods that work and those that don’t.
Having a deeper understanding of your prolific sources of traffic, sticky pages, underperforming products, and best-converting offers, among others, can shed light on your successful sales and missed opportunities.
7. Gaining Awareness of Consumer Sentiment
Responding to customer demand has been a major challenge in the past without an efficient tool to keep up with what’s trending among consumers. Fortunately, those days are gone.
Otherwise known as opinion mining, sentiment analysis is an elegant solution to discover emerging food trends. With the right tools, you can find out the dishes and drinks people are raving about on social media. If you leverage your knowledge of what’s hot and what’s not, you’ll be able to adapt to demand changes quickly.
8. Nailing Personalization
Consumers are not the same. And painting them with the same brush will inevitably alienate some groups.
Data analytics can aid your micro-segmentation efforts, helping you generate more revenue from customers who don’t spend much and instill loyalty in those who frequent your food establishment.
Through data mining processes, you can find out what makes different demographics tick. You can segment them by visit frequency, order value, price sensitivity, taste preference, and other factors.
Once you gain a deeper understanding of each group, you’ll be able to personalize your marketing efforts to keep them engaged. If you do it right, you can minimize the risks and capitalize on the opportunities associated with each demographic.
9. Automating Report Generation
Reports expire. Since they’re critical in decision-making, you can’t afford to lay your hands on something outdated..
A good data analytics solution crunches the numbers in real time and presents the findings in a digestible format. Frictionless report generation can positively impact your ability to choose one option over another on the fly.
Further, the automation of report generation provides management flexibility. Imagine the convenience of being able to see the health of your business through updated documents accessible anytime, anywhere.
10. Comparing Locations
Planning to move to a better area or open a new branch? Advanced analytics can help you pick the perfect piece of real estate to relocate or expand.
With so many prime locations to consider, relying on intelligent software to narrow down your options based on prospective footfalls and potential sales can make your life easier. Likewise, data-driven site selection lends more confidence in decision-making.
In Conclusion
The use cases for data analytics in the F&B industry aren’t limited to the contents of this piece. Actually, the practicality of an analytics solution can reach as far as your imagination will take you. The adoption of this tech is a question of when, not if, so waste no time to stay ahead of the curve and reap the benefits of running a data-driven food business.