Why the customer is not always right
Consumer behavior on food logging tools reveals that initial expectations do not match actual experience.
We all have the best intentions in life, whether it’s reading more, hitting the gym regularly, or watching what we eat. But maintaining those goals isn’t always easy or straightforward. Fortunately, a growing number of apps are designed to help us better track and achieve our ambitions.
With target gamification and leveraging behavioral techniques such as nudges, prompts, and prompts, these apps can help keep an individual focused on hitting their targets. But how well do they work and how can they be designed for optimal efficiency? Moreover, does the behavior of the users correspond to their initial expectations?
In recent research conducted with my colleagues, Jackie Silverman, Kristin Diehl and Gal Zauberman set out to investigate this through the study of food journaling tools, and how different techniques – in particular, photo-based journaling by compared to text-based logging – affect consumers. ‘ Perceived and actual logging behavior and experiences. Our findings suggest that while people have a clear idea of what will best help them achieve their goals, those expectations don’t quite match reality.
Consumers with healthy dietary goals are often encouraged to record their food intake. Food journaling is associated with greater success in avoiding unhealthy foods, and previous research has documented a positive link between journaling frequency and weight loss. Of course, this must be done consistently to be effective – which can be a challenge in itself.
Our research investigated whether the food logging system used had an effect on anticipated and actual user behavior. We were particularly interested in any potential disconnect between what people believe is the ideal way to log their food intake, versus what they actually find to be the most effective tool for driving long-term adoption in the practice.
In a study of 425 participants who all wanted to monitor or change their eating habits, we asked them to consider two food recording services. One asked them to record their consumption by taking a picture of their meals or snacks, and the other by entering a text description.
As we predicted, participants were more likely to opt for the photo-based method, believing it would be more useful in helping them achieve their goals compared to a text-based tool. They also thought the photo-based option would be easier, faster and more enjoyable to use, and they would feel more compelled to keep logging meals in the future.
However, this was not true in practice. In a separate survey, we asked hundreds of participants with similar food-related goals to record their food intake for a week using a photo-based tool or a system based on of text. Compared to those who performed text-based journaling, those who performed photo-based journaling ended up reporting a lower total amount of their food intake. They also felt less inclined to continue logging after the study and had a more difficult and less enjoyable experience.
Our results reveal a disconnect between anticipated and actual consumer behavior, which offers insight into the differences between how individuals approach the pursuit of a goal and the factors that affect them when it comes to pursuing. It also illustrates the tendency for people to make forecasting errors – in this case, incorrectly predicting what they imagined would best help them achieve their diet-related goals.
Photo-to-text recording: the reality
There are myriad possible reasons why study participants were more likely to select a photo-based tool. For starters, pulling out a smartphone and recording an image with a simple tap might seem less tedious than typing out a description of their food. They also might have expected images to more accurately document what they were eating. After all, a photo can capture a complete visual representation of a meal or snack. Achieving the same wholeness through words may seem more difficult.
Smartphones and social media have also allowed people to take pictures of what they eat, and photo-based journaling can be seen as a natural extension of such enjoyable everyday behavior. Additionally, taking photos – compared to writing – could also provide a more vivid and immersive experience. This can lead to positive associations with the act and make users believe that they would be inclined to continue the behavior in a logging context.
However, as our results show, photo-based journaling can actually hinder progress toward goals. An important reason for this could be the tricky time aspect: photo-based journaling needs to be done within a precise and narrow timeframe to be effective. But sometimes users just forget to take a picture; are distracted by other routines or interactions; or are so hungry that they start eating before they remember to take a picture. Once this happens there is no going back and their food record sequence is compromised.
Breaking a streak can be an extremely demotivating and anxiety-provoking factor that hinders the respect of objectives. While gamification of such logging behavior might sound great when consumers are on the right track, it can also backfire if there is no way for them to remedy any mistakes.
Compared to photo-based journaling, an important advantage of text-based journaling—which could explain the higher adoption and satisfaction rate among study participants—is that it can be done from asynchronously. Forgot to check in your sandwich before eating? Using a text tool gives you the flexibility to do this later and get the same results.
Indeed, while it’s usually difficult to remember to document your food intake, having to do it on the spot — or risk breaking a streak — presents an additional challenge. Therefore, photo-based records may contain a lower proportion of people’s total consumption than text-based logs, making them less useful to consumers.
Although our results show that text-based logging is currently more effective at tracking food intake, new advances in AI could make photo-based logging more sophisticated and improve user experience.
For example, companies could invest in AI technology that enables photo-based software to provide information that text-based tools cannot. This can include detailed summaries of calorie counts, portion sizes, and nutritional data, which can be gleaned from the image a person uploads to the app.
Individuals could leverage this information to help them make better decisions about their food intake and goals. It might make up for the more cumbersome aspects of photo-based journaling — though they might not be swayed if the benefits don’t outweigh the hassle.
Optionality is key in the long run
Our research offers several suggestions for companies building food logging apps and apps in general. While a photo-based tool may initially attract consumers, a text-based system is more likely to provide greater value and encourage them to stick around.
People can mispredict what they want or how they’re going to behave, and their intentions don’t always match their logistical realities. Offer both options – what users think they want, and what they Actually find more useful to facilitate goal pursuit – could maximize consumer adoption and user retentionwhile leaving individuals the freedom of choice.
It will also be essential for developers to combine the two tools in a seamless interface, such as making photo-based logging and text-based logging consistent. Users could then switch between the two – like when a photo-based recorder forgets to take a photo of their food and has to record it using text – without feeling a sense of failure or the perception of a streak. interrupted.
Ultimately, our research suggests that offering both photo-based journaling and text-based journaling in a single food journaling app may be the ideal approach. This would entice people to download the app and stay the course, creating a win-win situation for both the business and the consumer.
Alixandra Barach is Visiting Associate Professor of Marketing at INSEAD. She is also an Associate Professor of Marketing at NYU Stern School of Business.
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