How to quickly gain new knowledge about how your competitors are promoting their brand? In the material, we will reveal this issue and tell you how to effectively conduct competitive analysis, how AI will be useful, and how to use the obtained data correctly for an advertising strategy.
When solving any non-trivial task, as a rule, we are faced with both pluses and minuses of implementation. If we talk about the pros of AI-based competitive analysis, then the positive point is that everyone has data that is in the public domain. We can easily collect information about competitors in terms of the presence of advertising – whether they run TV ads, Performance ads, media, audio or video ads.
The downside to this task is the amount of information that needs to be analyzed. Suppose that we know about the fact of a competitor’s ad release and have collected the creatives, advertising videos, and audio tracks of interest to us. In this case, a natural question arises: how can you quickly analyze the amount of data that has been collected?
So, if we are talking about competitive analysis, then we are interested in the following information:
- If this is an analysis of banners, then we will be interested in what USPs are used by competitors, what attributes (emotional and rational) use to attract the audience’s attention, what objects are on the creative, what advantages are described by the text.
- If this is a video ad, then we will be interested in similar attributes – USP and objects. But here, in addition, it becomes possible to analyze the attributes that are placed in the text and offscreen voice messages at the time of the video playback, with which you can analyze the atmosphere of the video itself. It also becomes possible to collect information on the slogans that companies use in their videos.
- If we are talking about audio advertising, then here we can also transform the audio track into text and, based on the text information, compose an analysis of USP, emotional and rational attributes, which are emphasized in advertising.
As soon as we have the opportunity to parse information on each format within at least one competitor’s brand, we get additional analytics that will help us differentiate ourselves from the competitor in terms of advertising strategy. If we have the opportunity to build such analytics for ten or more competitors within one vertical, we get market analytics, which gives a huge advantage in terms of developing a communication strategy for the brand.
Why is AI needed in the framework of the task of analyzing the competitive field
Artificial Intelligence is a powerful tool for transforming huge arrays of creatives, messages, attributes and meanings into text information. The task of the automated process is to send the analyst a file with text that was removed from a text block located directly on the creative itself, or text that was removed from a voice or video format.
The advantage of this approach is the automation of the collection and detection of information. As a result, the analyst receives a full-fledged document with detected objects and additional attributes, on the basis of which it is already possible to build additional analytics, extract meanings and insights. Just imagine how much time it would have taken to manually review all competitors’ creatives, videos and listening to audio advertisements if it were not for the ability to connect neural networks to automate such tasks.
What tools to use to detect information from different advertising objects
We have our own Valery parser, which allows us to collect, detect and analyze objects, breaking them down into various attributes. There are also similar algorithms on the market that allow you to perform some of the functions. This and Google Cloud Video Intelligence APIthat recognizes objects in the video. AND Google’s Vision AIwhich allows you to perform similar operations with creatives, etc.
It is more convenient for us to use our own custom solutions for the reason that this way we can remain more flexible, and leave the opportunity to adapt to different kinds of client tasks.
AI-powered competitive analysis examples
Of course, when we talk about competitive analysis, there are many tricks and sides from which one can approach the solution of such a problem. With the help of Valeria’s parser, we close only one data analysis block, which is more focused on the direction of working with a creative concept and expertise in a strategic direction.
So, for one of the clients of the auto segment, we have prepared a market overview in the context of 11 car brands. Only the video format of YouTube ads was analyzed.
To obtain representative conclusions for each brand, at least 2 videos were analyzed for each model within the brand. As a result, having studied 66 videos on 34 models of various brands, we gained new knowledge that, for example, in 74% of videos, brands use voice guidance along with text attributes. In 41% of cases, technical characteristics of cars are mentioned as textual accompaniment – more than 5 such characteristics are found in the videos of Volkswagen Jetta, Hyundai Elantra and Sonata, Kia Optima, Toyota RAV4 and C-HR, Volkswagen Tiguan, Nissan Murano, Skoda Kodiaq, Audi Q7.
After conducting such an analysis of competitors, we were able to collect all the brand slogans for each car model. The parser also helped identify accents on emotional and rational attributes. For example, one of the German brands, within the framework of promoting a certain model, focuses on adapting to changes, convenience, comfort and functionality, while when promoting another model, emotional and rational attributes prevail, related to fashion, style, dynamics, travel and freedom.
Against their background, the positioning of the Japanese brand looks different, which in the framework of promoting various models uses similar attributes: manufacturability, speed, novelty, design and reliability.
It was interesting to draw up a general map of brands that convey their values through advertising videos in completely different ways. Seeing the complete picture of the positioning of competitors in the market, it will be quite easy for a company to navigate further tactics of promotion in terms of developing a creative concept.
Another example is from the real estate industry. As part of the analysis of the competitive environment, the task was set to identify rational and emotional attributes in order to highlight a tactical hypothesis, which can develop into a strategic vector. We have analyzed 21 development companies in the Moscow market. We took banner and audio ads for analysis. After that, we identified rational and emotional attributes, breaking them down into strong and free attributes.
So, as a result of competitive analysis, we have a ready-made framework for prompt response in the market, which allows us to measure the state of clutters for prompt adjustments in the strategy.
This kind of competitive analysis is just one form of data analysis that can be used to find new knowledge, patterns and insights.
At the moment, it is important to analyze the competitive field in order to strategically be one step ahead of the competition. When making decisions, you need to know and analyze what is happening in your niche, periodically looking around 360 degrees. To do this, it is worth conducting a competitive analysis every 3-5 months, each time making a different cross-section of competitors, measuring the dynamics of changes. We recommend conducting this kind of research for any industry where there is a wide field of players – pharmaceuticals, services, FMCG, real estate and auto, financial, etc.