Leveraging Insights into Menu Item Performance, Brand Affinity, and Price Sensitivity to Improve Financial Results
Whether the goal of your next menu project is to ease operations and enhance productivity through streamlining, or to infuse new life into your menu through product innovation (or some combination of both), your chances for success can be dramatically enhanced by considering and incorporating multiple data points in a comprehensive approach.
Outside of consistent operational excellence, menu optimization initiatives are one of the most powerful levers operators can pull to drive business results across their system. As the “Information Age” advances and the amount of data generated increases exponentially, finding relevant and actionable insights to optimize the menu becomes more complex.
Accordingly, many restaurant companies have turned to specialists who are experienced in navigating brands through this swirling sea of data to make sense of it all. An experienced Menu Optimization expert not only knows restaurant data, but can provide strategic guidance, define best practices, and offer tips and tactics that have proven successful in meeting the business driving objectives of multiple menu initiatives. And unlike traditional menu engineering, preferred providers use contemporary tools, data sources, and methods to ensure a comprehensive approach that minimizes risk and maximizes your return.
Where Traditional Menu Engineering Goes Wrong
Historically, traditional menu engineering has always included an evaluation of each menu item’s performance, usually in terms of price, quantity sold, and item cost. From these basic data points, one can easily calculate and evaluate each item’s contribution to overall sales and profits. A basic comparison of relative product velocity to profit contribution can identify “stars”, “dogs”, “puzzles”, etc., from which under-performing products can be selected for deletion or potential replacement, and top-performing products can be featured or emphasized. While this explanation is over-simplified, there are a number of menu software packages and consultants that can do this for you.
This simple method has long been used by operators to make decisions about additions and deletions, but fails to address an important point of potential risk that in prior decades was much more difficult to access. Specifically; What if a low-velocity product, that would otherwise be a candidate for deletion, has a small but distinct audience of consumers that come specifically for that item?
In marketing, this concept is called “unduplicated reach”.
Traditional menu engineering ignores that a low-volume menu item may have a distinct following, making the false assumption that all consumers are the same, and that low-volume means low-traffic. If that low volume product does draw a distinct audience, deleting that item may cause a disproportionate traffic loss when only traditional item performance measures are considered.
A Consumer-Focused Enhancement to the Traditional Model
Using contemporary research methods and analysis tools, smart menu managers can also identify the role each product plays in driving unique customers and increased frequency, and understand this previously unconsidered risk of removing underperforming items. Additionally, new product concepts can be tested in the same way to identify menu items that are most likely to generate appeal, and traffic increases. This consumer research is often referred to as a TURF study, an acronym for “Total Unduplicated Reach & Frequency.”
The result of incorporating a TURF study into menu engineering is an enhanced decision making process that considers both product performance and traffic and interest driving attributes, or “affinity”. Contemporary research tools and software has made collecting and evaluating this information much more efficient, and therefore less costly.
A Price Sensitivity Enhancement to the Traditional Model
The traditional menu engineering grid also implies that one remedy for a high-volume, low-margin item is to improve the item margin, often times by increasing the price. But what if that item is price-sensitive or is priced above directly competing items in the market? Or what if it is also a high-appeal, traffic-driving item? Presumably, knowing these characteristics of the item would affect your decision regarding a price increase, and potentially direct you to look for better opportunities elsewhere on the menu.
Likewise, decisions whether to promote a high-margin, low-volume item should consider affinity and sensitivity measures, and can guide marketers to selecting optimal products to promote. Products that are highly sensitive (i.e., will respond to a lower price) and have high levels of brand affinity (i.e., attract an audience) are the ones that are most likely to drive traffic, especially if a market-relevant price point is used as an incentive.
Knowing each product’s profile in terms of performance, affinity, and sensitivity is critical to making well-considered decisions regarding menu changes, and can aid in making better, more profitable decisions about the menu layout, promotions, LTOs, media content, and pricing.
This blog was written by, Ted Babcock, VP Analytics Services