Why Restaurants Are Measuring Speed Of Service Differently In 2023
“It takes months to find a customer and seconds to lose one.” – Vince Lombardi
The restaurant industry is in the midst of a mass migration from the old school to the new school. From barebones tech to high-tech tools. From gut-feeling to hard data.
And in this shift to a more modern, higher-velocity operation, where does “speed of service” — a long-standing operational efficiency metric that’s highly correlated to customer satisfaction — fit in all of this?
That’s exactly what we’ll look at. We’ll see why it’s of growing importance, the traditional ways of measuring the metric, and how restaurant brands are measuring service speed differently.
Why Speed Of Service Matters More Than Ever
When you boil a restaurant down to its most fundamental elements, you have three value propositions – desirable food, timely delivery, and quality service. And in today’s world, there are far more restaurants serving great food by way of pleasant staff and far more impatient customers.
Thus, it’s boom or bust when it comes to service speed. Let’s look at why it’s more important than ever.
Highly-Competitive Restaurant Space
Per Global Data, The entire restaurant industry in the U.S. will hit $1 trillion in yearly sales across over a million restaurants in the next few years. The space is so vast and the pie is so big, that even behemoth brands with 500+ locations look like a drop in the ocean.
And if they look small, then the mom & pop shop down the street could be rendered subatomic.
Yet, here everyone is, trying to make tech improvements, master multiple delivery channels, and stay afloat in the vast sea of competition. While restaurants are fighting to survive, they’ll discover that optimizing wait times – even by fractions of a percent – can ultimately become a key component to growth.
In the same way that the attention span of society has nearly dropped below that of a goldfish, so too have we become more and more impatient during periods of extended waiting. This is the reason most restaurants have multiple ordering channels – to provide guests a means by which to get their food faster and in a way that’s more suited to their buying habits.
In fact, Market Research Future (MRFR) did a study on wait times and found that our instant-access, instant-gratification, and instant-ordering age has caused the average person to overestimate their wait time by nearly 40%.
Improve service speed, increase revenue. It’s that simple.
The MRFR report says that while the average restaurant’s revenue would increase by nearly 15% if waiting were eliminated, 30% of restaurants are reporting that waits are actually getting longer for guests.
This could be due to a variety of things – internal and external to the operations – but the overarching theme is that there is a golden opportunity to outperform the competition in the speed category and take home a bigger share of the bacon.
Nearly 75% of people say they spend more with a company who has a history of providing positive customer service.
American Express, 2021 Poll
Where The Old Ways Fall Flat
In order to get to the bottom of speed of service issues, restaurant brands must be able to garner a sizable and consistent stream of granular guest feedback data – size for statistical significance and consistency for routine measurement.
Over the past few decades, mystery shopping companies and traditional customer experience management platforms have stepped up to the plate with a goal to deliver the aforementioned guest feedback.
But going into 2023, they’ve fallen behind.
A mystery shop provides evaluations of businesses by assigning secret shoppers to visit and assess customer service, product offerings, and overall experience. Their feedback is analyzed to provide insights and recommendations for improvement, with the ultimate goal of improving customer satisfaction and driving additional sales.
Now, let’s examine three ways in which mystery shops are being reconsidered by restaurant brands in 2023.
Mystery shops charge anywhere between $50 and $200 per report. This is an extraordinary amount of money to expend for one individual’s feedback, especially given that the auditors are almost never regular patrons. The cost is even more intimidating when accounting for all locations and over the course of an entire year.
The final deliverable of an auditor is either one of two things – the results of a lengthy questionnaire or a multi-page executive write-up on their experience. While these can be detailed and helpful, it is in no way scalable. A review process will have to take place with each one of these reports, stripping valuable time from executives, general managers, and location-level teams – all for information that should be easily processed, organized, and stored in a filterable online report.
When a mystery shop produces a monthly report several days after an auditor visit, the restaurant will see a one-hour snapshot of a single delivery channel for that 30-day period. The other 729 hours in a month are unaccounted for and one, two, three, or four other delivery channels are left out. Combined with the fact that most mystery shops use cross-vertical reporting templates, the insights aren’t of the quantity or quality to realistically improve.
Traditional Customer Experience Management (CXM)
Customer experience management platforms like SMG, InMoment, and Medallia are software solutions that have been around for decades, looking to combine feedback sources into a single platform and improve guest satisfaction.
Here are the three reasons restaurants are beginning to move away from long-standing, traditional CXM platforms.
Because these platforms cater to a wide range of industries, the metrics available to restaurant brands are far more generic in nature. There are only a handful of operational categories to enlist and no sub-categories (root-cause factors) that drive true actionability. In addition, the survey data that populates the dashboard is only a few basic questions, which means that not nearly enough insight is collected in order to drive decisions at the brand or the location-level.
Traditional CXM platforms are well-known for their clunky dashboards and difficult learning-curve, appealing more to data analysts than the average restaurant operator. This increases the friction in brand-wide adoption, due to the increased time spent in training, and significantly lowers engagement rates DMs and GMs.
Once a restaurant brand is up and running with one of the aforementioned CXM providers, they tend to be forgotten. There are no strategy and insights sessions that help members of the executive team find new trends or spot ongoing patterns in the experiences of guests. Flying blind isn’t a pleasant experience.
What The New Way Does Right
A few years ago, Tattle worked with a restaurant brand that really struggled with speed of service.
We worked with them in trying to rectify the issue, taking into account each bit of feedback, having their locations do anything from adding more line cooks to reducing overall menu selection. We watched the feedback roll in around this category as we made changes, hoping that something would stick and settle the issue.
For a while, nothing did stick. Then one day, a Tattle survey said something quite eye-opening. In survey’s category-specific text box – where patrons have the option to write greater detail about their ratings for Speed of Service, for example – one individual wrote the following:
“I hate to rate anything low for you guys, because the staff was really fantastic to my family. But the food took a while to come out. Maybe 15-20 mins longer than I would have expected.”
That gave us an idea for this particular brand. Instead of working to shave additional minutes off the wait time through operations, what if we shifted our focus to altering the guest’s overall perception of the wait time?
Because the staff had been rated so highly on Tattle scores and was even being lauded in low Speed of Service reviews, we came up with the idea to hang posters all across the dining area of the chefs, wait staff, management, and brand. We talked about their journeys, accomplishments, and values. Anything that could garner empathy surrounding the restaurant operations, we plastered on the walls.
And it worked.
Their Tattle Speed of Service ratings went up in the following weeks as the brand and its teams were humanized. Customers felt the longer wait was justified because good, honest people were doing the best they could to get out quality meals in a timely fashion.
Without the consistency of data (where mystery shops fall short) and granularity of insights (where traditional CXM falls short), we never would have been able to solve this problem as quickly or as effectively as we would have otherwise.
Only because the Tattle platform collects guest feedback that is high-volume, granular, and consistent – funneled through a simple, intuitive dashboard – were we able to help this brand improve their service speed, retain customers, and generate more revenue.
In fact, Tattle overcomes all of the primary deficiencies of mystery shops and traditional CXMs by doing the following:
- Collecting survey data from real customers, at scale
- Collecting highly-granular data from each survey
- Driving action with root cause analysis and team-level objectives
- Providing an intuitive, restaurant-exclusive dashboard
- Being extremely cost-effective
- Being an engaged partner
The Tattle Difference
Before covering what Tattle measures in relation to service speed, here’s a quick overview highlighting how different our platform is compared to the rest of the solutions on the market.
Tattle stands apart from the generalistic auditor reports and CXM metrics, being built exclusively for FSRs, QSRs, and Fast-Casual brands. Every one of our operational categories and subcategories are tailored to the needs of restaurants and are the foundation for improvement. These metrics can be customized even further to better align with the food vertical.
The more data, the better – and we have mastered the collection process. Our surveys are 55+ questions and garner a 10% participation rate and a staggering 94.3% completion rate. The plethora of insights each brand collects are viewable in an easy-to-use dashboard that allows for granular filtering (by groups, individual locations, daypart, team member, menu item, and more),
Tattle doesn’t leave GMs and location-level teams high and dry with a bunch of feedback data. While the reporting alone is actionable enough, we opted to go many steps further, giving them intuitive tools in order to directly interact with guests, resolve customer complaints in real time, and align their teams to measurably improve satisfaction with Tattle-curated objectives.
When it comes to speed of service, there is a delicate balance to strike. If delivery is too fast, order accuracy and food quality – particularly temperature – are at risk. If delivery is too slow, the overall customer experience rating is at risk. With the copious feedback Tattle collects, restaurants can find the optimal service speed that keeps all other categories at healthy levels.
Customer Success Manager, Tattle
How Tattle Measures Speed Of Service
Within the Tattle dashboard, there are many different ways of dissecting the Speed of Service category, from a macro or micro view.
Let’s take a look at the real-time, filterable macro views:
- Group of multiple restaurants (can group by owner, region, etc.)
- Individual locations
- Specific dayparts (lunch, dinner, night, etc.)
- Specific delivery channels (dine-in, takeout, pick-up, etc.)
- Specific date ranges
Now let’s turn our attention to the best part – the root-cause identification factors. These can be customized depending on the needs of each brand. Below are some of the most common factors that restaurants measure across a variety of delivery channels.
- Ability To Find Hand-Off Destination
- Drive Handoff Experience
- Estimated Delivery Time
- Estimated Wait Time
- Order Confirmation
- Order Ready Upon Arrival
- Payment Processing
- Time Spent Making Online Order
- Wait Time To Pay
- Waiting For Ordered Items
- Waiting In Line
- Waiting To Be Seated
- Waiting To Place Order
During the survey-taking process, each customer will be able to peg factors as either good, neutral, or bad and have the option to leave a comment explaining their rating. Those with a negative rating will appear within the dashboard’s factor details, allowing teams to quickly view and remedy those problems.
When these factors are combined with macro filters, the data can become incredibly targeted and refined. This will ultimately eliminate any knowledge gaps in the Speed of Service category, allowing for maximum visibility and zero guesswork.
The usefulness of this factor-level data is multi-dimensional, affecting both the nuances of guest satisfaction and revenue correlation.
For example, over a day, it can allow teams to quickly fix problems in real-time.
Over a month, DMs and GMs can identify factors that lag behind and target them in isolation.
Over a year, executives can garner long-term, large-scale trends or deficiencies, driving brand-wide business decisions to ultimately improve unit efficiency and growth.
This is the depth and breadth of data that restaurant brands are looking for.
The speed category hinges largely on guest perception, with Estimated Wait Time always winding up the most negative factor. While food can be made objectively fast, if the wait time exceeds the 25-minute wait shared by the restaurant to guests for their pick up or delivery order, waiting an extra five minutes can feel like eternity.
In the increasingly competitive and high-tech restaurant sector, the cracks are showing in the decades-old feedback solutions.
Tattle is doing customer experience differently, providing a platform with the primary goal of restaurant improvement – not to collect data just for the sake of it. And the Speed of Service category we look at here is just one of a dozen categories Tattle is capable of measuring (Food quality, order accuracy, hospitality, etc.).
Everyone – from the CEO to the line cook to the guest – wins with an improvement mindset.