Askia is delighted to announce that the Brand Coding module of codeit is now available to all users with the ‘Essentials’ version of the platform. This module has been available for a few years now and has proven itself to be extremely productive when coding brand names in market research surveys, but this was only available in the premium ‘Explorer’ version. This commercial change opens this important functionality to all codeit users.
So, what are the challenges of coding brands and how does codeit help?
In the realm of market research, companies are often driven by a strong desire to measure the saliency of the brands they own. Typically, this is achieved through spontaneous awareness questions. For instance, a common question might be, ‘When thinking about car brands, which ones come to mind first?’ Respondents are then expected to list several brands that spontaneously come to mind. This kind of questioning serves as the definitive test of brand salience because it measures top-of-mind awareness.
However, the task of analysing the data collected from such questions is not as straightforward as it may seem. While it might appear easy to count the number of mentions of each brand, possibly using a pivot table in Excel, the complexities encountered in real-world applications tell a different story. This blog post outlines the common challenges in brand coding and how the codeit platform can help manage such data effectively.
Common challenges in brand coding
1. Misspellings of brand names
Survey participants frequently make errors when typing brand names, due to either inattention or the inherent difficulty in spelling certain brand names, such as ‘Lamborghini’, ‘Schwarzkopf’, and ‘Häagen-Dazs’. It is crucial that all mentions, including misspelled ones, are accurately coded and counted. The dedicated ‘Brand Coding’ mode in codeit employs specialized AI to identify and group misspellings with correct brand mentions, simplifying the review process and enabling efficient coding of numerous verbatims in one go.
2. Ambiguity, vagueness, and slang in survey data
At times, respondents provide answers that are not the clearly defined brand names expected. Responses can be ambiguous (e.g., ‘Galaxy’), vague (e.g., ‘Virgin’), or include slang and colloquialisms (e.g., ‘Macky D’s’). Resolving and coding such responses typically requires human judgment, based on the research objectives, subject matter, and survey purpose. codeit’s human-led approach ensures that these decisions remain in your control, allowing human coders to efficiently address items that AI cannot automatically code.
Resolving and coding responses like this is usually a judgement call. It requires a real person to adjudicate – based on the research objectives, subject matter and the purpose of the survey. codeit’s human-led ethos means that you are always in control of decisions like this. It’s quick and easy for a human coder to review items that can’t be automatically coded by the AI and take the necessary action.
3. Multiple brand mentions in survey responses
For questions that allow multiple brand mentions, ideally, each brand should appear as a separate verbatim entry in the data. However, respondents often list multiple brands in a single response, such as ‘McDonalds, KFC, Burger King’. Longer responses like these are more challenging to manage and code than single-brand mentions. To address this, codeit’s Brand Coding mode can automatically split these into individual items, allowing coders to handle each brand separately, greatly enhancing efficiency.
The role of generative AI in solving brand coding challenges
Although there is much discussion around the potential of generative AI, its effectiveness in resolving brand coding challenges is limited. Large Language Models, while useful, perform inadequately due to the complexities associated with brand coding. We believe that our specialized AI, crafted for brand coding and supervised by human coders, delivers the fastest and most reliable data when coding brands.
Next steps?
If you are facing difficulties with brand coding and are seeking the most effective solution, then get in touch with us to discuss how codeit can help.
