Today’s QSRs are faced with so many challenges - it’s no longer enough to just deliver great food at a great price with great service. Digital challengers, delivery services, greater adoption of mobile and the challenges posed by Covid-19 have rocked the entire industry.
The top performers in QSR have overcome these challenges and even grown by partnering with the right technology and strategy platforms.
Modern QSRs are using new techniques to increase repeat visits, convert deal-seekers into loyalists and encourage upmenu exploration – all contributing to an increase in single-store sales volume while minimizing promotional margin contribution loss.
Collectively these tools and tactics combine to create a strategy called product intelligence:
- getting real time insight into operational performance across digital and in store
- mapping that performance to the actions and behaviors of their customers to identify the highest performing customer segments
- bringing it all together to enable rapid, confident decision making that increases profit and volume
Unifying signals from cross-channel experiences
The start of any product intelligence initiative is in bringing all of the data together. Remember, customers experience a cohesive brand – they don’t differentiate between the in-store experience, the app, or the commercials that contribute to the brand voice. They expect them all to work as one integrated offering.
So it’s important to be able to visualize the customer journey all in one place by uniting events across channels. A Facebook ad that leads to an app install that encourages an online order that’s picked up curbside all contribute to a single job in the customer’s mind: getting lunch.
To instrument all of these signals it’s critical to have a product intelligence platform that can ingest and graph all of these events as a single stream.
Once franchise-wise data is consolidated into a “single pane of glass” analytics tool, it’s easy to get an immediate view into the impact of promotions, compare today’s or this week’s performance against historical baselines, and even forecast future promotional activity.
Modern product intelligence tools like Amplitude are different than the “weather reporting” tools of the past. They don’t just show what happened in static, fixed graphs. Instead, they use a model called event streaming, where every blip of information is immediately available for analysis.
This lets operators do away with complicated SQL queries and the two-week “ask the BI team to pull a report” cycle. With product intelligence tools, graphs are built on the fly from simple to understand drop down menus.
It’s one click away to switch from viewing milkshake sales over the past 90 minutes to viewing the past 90 days. One more click and you’re comparing west coast to east, Kansas City to St. Louis, or store 161 to store 242.
Suddenly operators start realizing they have so many more questions and find that asking the right questions is as important as having the right answers. Did our “25% off a sandwich” promo customers buy more medium or large soft drinks? Were combos more popular than single items? Did people order more items when the line was long, or short?
The other advantage is being able to use the data to predict future scenarios. With product intelligence, operators can now easily model the impact of a 20% promotion compared to offering a free side. They can see how promotions affect different dayparts, compare weekdays to weekends, and even see how holidays will impact sales.
This insight allows for better planning, less margin loss, and more transparency with franchise owners.
Identifying top customers and their actions
In analyzing product intelligence data across multiple top 50 QSR chains, we’ve consistently seen a common breakdown called the pareto principle, also known as the 80/20 rule.
Simple, this means that 80% of revenue tends to come from just 20% of customers. Those top customers visit more frequently, across a shorter period of time, and spend more per visit.
This is commonly broken down into a model called RFM:
- Recency of the last visit
- Frequency of visits overall
- Monetary value of those visits
While that sounds simple, it turns out that the behaviors that lead to high RFM aren’t always obvious. For some customers, it means coming in every morning for a milkshake, but only once a week for a meal. For others, it’s getting the same turkey sandwich every Thursday.
These behaviors combine to create purchase habits– and because they tend to be consistent, they allow us to analyze the data and identify the hidden habits that lead to more top customers, and greater sales.
Modern product intelligence tools collect more data than just what happened – they include all of the detail around an app session or web visit to provide context clues around a behavior.
Now, top QSRs are able to see that a customer who explores more of the menu, or spends more time reading a product description, may be more willing to spend on higher margin items.
Likewise, we can see the behaviors that point toward low RFM performance – deal seeking, “just browsing”, or one-time tourists.
Thus, QSRs can tune their product to encourage the behaviors that turn customers into loyalists, like making the “view ingredients” button more prominent, moving specialty items to the top of the drive through menu, or displaying a promotional card at the start of an app session.
Encouraging higher growth behavior
While using data for historical measurement is vital, where it really becomes powerful is when data informs future decisions. Once top segments are defined, performance-minded QSRs are creating custom targeted 1:1 offers that encourage positive, revenue-generating behavior.
These hyper-focused promos target users with exciting value as their RFM is declining, encouraging menu exploration, upsell/cross sell, or extra visit types (from breakfast to late-night, or from weekend drive-thru to Wednesday dessert hangouts).
But the promotions aren’t done in a vacuum or just shot from the hip; with the flow of event-based data, the performance of these targeted offers is measured and tuned in real time, and reinforced by nudge campaigns including custom email, push notifications, and social ads.
Marketing automation platforms integrated with the product intelligence can accept groups of users called “cohorts” that are hyper defined: “just customers who bought two sandwiches in a trip between June 1st and July1st and haven’t been back this week”. These cohorts are then added to intelligent workflows that target individual users at the time and channel they’re most likely to take action.
Through the use of cohorts, timing and omnichannel workflows, QSRs see their promotional dollar go further, their customer value grow, and their same-store revenues consistently rise.
A clear view to the future
With so many choices ahead – curbside pickup, whitelabel delivery services, direct-to-consumer subscriptions, grocery offerings, cloud kitchens – today’s QSRs are tasked with moving faster than ever into new unproven channels.
How can a savvy operator know when to take a shot and when to pass? By informing their decisions with product intelligence. These customer event data streams provide the backstory to justify future initiatives, grounding these actions in sound evidence and modelled prediction. Suddenly a move that seemed risky becomes a clear safe bet– but the move that everyone else in the industry rushes toward may be revealed to be a dry well.
Product intelligence doesn’t just tell you what happened – it gives QSRs clear vision into their 3, 6, and even 12 month plan and incorporates broad shifts and major dips. Empowered with product intelligence, the best chains are having better conversations with more clarity and trust between the franchise and the operations, leading to more great customers, better strategic insight, and growth across the board.
How to make it happen
Product Intelligence is hugely beneficial - but it doesn’t all come together overnight. The best QSRs bring in a partner with experience to avoid the potholes and get to better action in the shortest amount of time. Even more so, they’re looking to partners to help them improve their data fluency, spreading that learning across their org to make sure every contributor understands and is able to take action from the data.
World Wide Technology is the premier partner for product intelligence in the QSR space. We sit on the same side of the table as our clients, helping them make the right decisions and take the right actions to gain product intelligence advantage.
A typical engagement with WWT involves mapping existing data sources, identifying gaps, and grounding the entire engagement around stated, clear business outcomes. We focus our efforts on measuring and instrumentation that ties directly to margin enrichment.
To get there, we work with clients to help them select vendors in the space– purpose built, best-in-class tools to analyze data and enable immediate action.’
Once selected, we bridge our clients’ infrastructure and the vendor customer support teams, creating an implementation plan that tracks all of the key events and their properties in a format that will flow across tools, eliminating rework from the start and providing clarity and ease of analysis.
Along with that, we help create “chart starters” – key business-outcome driven charts that measure the heartbeat across the organization and reveal top customers, their actions and the steps that can be taken to increase the recency, frequency, and monetary value of their visits.
To take it to the next level, our data team partners with our client’s business intelligence to create new models and reports based on raw data and processed with the latest algorithms. This deep analysis provides a foundation for later product intelligence work and creates a durable competitive advantage in the form of deeper customer knowledge.