The price is right
Headquartered in Toronto, Canada, PSL has a network of consultants around the globe with international offices in London, Singapore, Boston, and Mexico City. Since the company’s inception in 1993, they’ve delivered over 1000 projects to clients from over 25 different industries.
The ask

From Offline to Online
When we were approached by PSL, they had developed their own offline solution to help their clients with their pricing strategy. While the software could handle all of the complex calculations in an offline environment, it had limited access to multiple users, and there was room for improvement on the usability side.


“Refreshing the data was a big problem.” as VP of Pricing Analytics Fred Puech recalls. “Every-time you changed something in excel, there were complex formulas that broke. The software that we had built could only support one user at a time, which was the main limitation of being offline. What we wanted was for multiple users to be able to use the tool simultaneously.” Puech further emphasized the importance of this accessibility in reference to how franchises operate particularly in the United States. Under US federal law, franchisees in the US set their own prices. As such, in order for it to be used efficiently, the tool would need to be made accessible to all of the franchisees as well as executives from restaurant headquarters.
How we helped

The power of discovery
Discovery sessions are always important, but its value becomes even more apparent in a complex project such as this. Before we created any plans, we sat down with PSL to fully understand their business and fully analyze the existing software. We conducted a series of workshops which gave us clarity into the product vision, product goals, user personas, user journeys, and product features
The results from these workshops then informed the priority of the features we needed to build and the trajectory of the project.
We identified 3 categories of users for the MVP:
PSL Administrator
Restaurant HQ
Franchisee


How it works
PSL’s proprietary mathematical model, MenuPriceOptimizer™, was developed over years of gathering industry data and looking at trends on how pricing has influenced buyer behaviour and decision making. We took this existing solution, and created an online web app with a sleek user interface
The tool has two main functions to help franchisees or restaurant owners optimize their pricing strategy.
Simulation
MenuPriceOptimizer™ allows users to test out “what if” scenarios by making changes to the prices on their menu list. There are many factors to consider when making a price change to a single menu item, and the effects aren’t always obvious or direct. A single change could elicit any of the following effects:
Direct Effect
This refers to a direct increase or decrease in the volume of sales to the item that was changed. For example, if the price of a Chicken Sandwich was increased from $5.50 to $6.50, the sales volume on that item could potentially decrease as a result.
Substitution Effect
Using the same example as above, a buyer who has chosen to abandon the item “Chicken Sandwich”, might substitute that item with a different one on the menu. In the worst case scenario, the price increase could also cause a buyer to leave the store completely and potentially substitute the item with the same item from a competitor.
Basket Effect
The basket effect looks at the impact of how a price change affects the sales volume of a side item and other related items on the menu. If the item “Chicken Sandwich” was frequently purchased with a side of fries or a drink, the increase in price of the item might cause the buyer to forgo the sides. In this case, even though they’re spending more on the single item, the total amount spent in the purchase would be lower.



MenuPriceOptimizer™ takes all of the factors mentioned above into consideration and creates an output which shows the projected effects across the board. The user would then be able to see the potential impact a single price change could have to their business.
MenuPriceOptimizer™ takes all of the factors mentioned above into consideration and creates an output which shows the projected effects across the board. The user would then be able to see the potential impact a single price change could have to their business.
Optimization
In addition to the simulated projections, MenuPriceOptimizer™ can also suggest optimal presets for all menu items designed to maximize revenue with little to no impact to sales volume. Based on a vast quantity of past data, the software will provide four different suggested pricing strategies.
3%
Inflation
slight adjustment only to account for inflation with no change to revenue
6%
Recommended
slight increase to revenue with no virtually no effect on sales volume
10%
Moderate
average increase to revenue with little to no effect on sales volume
15%
Aggressive
higher return in revenue with slight impact to sales volume


Main challenges
Turning Data into Information
The complexity in this project lies in the pure quantity of variations on any given menu. Each client could potentially have hundreds of different menu items, each with their own variation. For example, a simple “chicken sandwich” could have different types of bread or toppings or add-on ingredients, and each variation could have a different price point. The total number of possibilities resulting from different combinations and permutations is far greater than what is typically seen on a menu. The challenge from a design perspective was to represent the vast quantity of data on the screen in a way that was easy to understand and intuitive to navigate.
Our designers started by identifying UX issues in the existing software. We then looked at the results from our discovery session (user personals, goals, features etc.), and revamped the UX and the information architecture to best facilitate the user journey. We consolidated the “simulation” dashboard by placing the pricing table and the dashboard in a single view. We also gave the platform a new UI treatment, making it feel more modern and minimalistic.

High Volume of Data
Working with big data in pricing presents its unique challenges when bringing the software from an offline environment to an online one. To date, PSL holds pricing data for hundreds of franchisee stores around the world. To put things in perspective, that equates to millions of rows in the pricing tables. When we’re dealing with a web application, there’s an expectation for an instantaneous response whenever an action is taken. This is also true for uploading large file sizes like franchisee reports. To keep performance high, and load times low, our engineers employed a myriad of tactics to optimize for speed. They created an asynchronous import process where the user can continue using the app while necessary files are being uploaded in the background.
Fred Puech
VP of Pricing Analytics
In short…
Through an in-depth discovery session, TTT Studios defined the necessary features for the MenuPriceOptimizer™, and delivered a high quality Minimum Viable Product (MVP).
TTT Studios brought the MenuPriceOptimizer™ from an offline environment to an online platform, making it accessible to multiple users.
The design team from TTT, revamped the UX of MenuPriceOptimizer™, making the app easier to navigate, and more seamless for its users to achieve their goals.
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