Behavior Insights
How to understand a Behaviour Insights Report
Last updated
How to understand a Behaviour Insights Report
Last updated
A behavior report is a type of insight built to analyze the habits of one or more audiences by means of various touch points. It is a directional attempt to paint the picture of your audience and understand the traits that they have developed over a period. Consumr.ai uses anonymized first-party and third-party audiences to calculate real-time data from various data sources connected to millions of users across the world and provides you with a report that can be used for media, creative, content, sales, and even overall business strategies. In this manual, we will take you through the ways of executing a behavior report and how to read the visualizations and act on the data to build plans and strategies.
As explained in the introduction, a behavior report is generated by unpacking 3rd party or 1st party audiences. In the current scenario, we consider interest segments that can be interpreted by various platforms as 3rd party audiences and lookalikes created on Meta, Snapchat, TikTok, and other audience platforms as anonymized 1st party audiences.
While selecting these audiences to prepare a report, you need to know the type of audiences that you have built on the platform. Creating reports with random audiences will not help in creating valuable insights and plans. For example, if you want to understand the behavior of consumers that are similar to purchasers of your product, you will have to select a lookalike created using a custom audience of purchasers. You can select one or more audiences at a time. For more details, refer to "How to use Omnibox Link". Once you are ready with your selections and click the Fetch Insights button, you will be taken to the behavior report. Read on to understand how to read this report in detail.
consumr.ai may look extremely simple, but what happens under the hood is extremely complex. Hence, it will take some time to load up your report. The platform is built for speed, but since it extracts real-time data from various sources, the output cannot be within seconds. Unless you enable the feature of Advanced AI from the Advanced options in the Omnibox, the system will first load up a standard report. To know more about Advanced options, please refer to our article on how to use Omnibox.
A standard report is a composition of cards that carries some basic information about your audience, like age and gender split, themes and interests, geographical concentration, that can be produced quickly. A standard report will give you the option to add on Advanced AI cards, that will have more dimension and information about the audience, though it might take a little longer.
When the report is in progress, you will see skeleton loaders fill the screen with a “Work In Progress” tag that will show you an estimated time with a countdown. Normally, the report populates way before the countdown ends.
Note: This card is a feature of Advanced AI and will not show up in a Standard Report.
This is the first card that you can see on the report. As one of the philosophies that ProfitWheel was built on, was to humanize data as much as possible. Consumers are real people and not transactions, hence it is only fair to make a summary that can paint a more realistic picture of how the audience will look using a Behavior Lens.
It shows a photo (created using AI), a name (also randomly generated) as per the gender. Both these aspects are also intelligently created keeping in mind the attributes of the audience, to get you as close to the impression of your consumers as possible. The rest of the details are shown based on the skewness in data. The more dominant characteristics show up in the card.
Looking at it, you can now visualize how your ideal audience would look like. Their education, job, and their habits with core interests. This helps you paint a picture of your audience and helps you humanize the data. Detailed analytics of each of these parameters are covered in the insight cards throughout the report, yet this card proves to be an incredible summary of the insight. Age & Gender Split
There are two visualizations for this insight. Overall, it shows the spread of your audience into various age brackets and between Male and Female, to give a fair understanding of its distribution. In the example above, it is evident that the demography is almost evenly balanced between both genders. It peaks at the age group of 18 to 34. The product gives directional signals in every visualization to let human intelligence pick and understand these nuances. For example, the significant yet dwarfed age group of 45 to 54.
Note: This card is a feature of Advanced AI and will not show up in a Standard Report.
The Stages of Life card is applicable to an Advanced AI enabled report. It distributes your addressable audiences into stages of life they are in. To evaluate it, we use relationship milestones, since relationships majorly influence the behavior of consumers.
Stages of Life uses a comparative bar chart to show you how your selected audience compares with the universe. To ensure that we do an apples-to-apples comparison, we equate the scales, in this case Reach Scores. 'Your Audience Reach Score' refers to your selected audience and 'Population Reach Score' refers to the overall Universe your audience is from. There may be many instances where you may see 'Your Audience Reach Score' going way higher than the 'Population Reach Score', which means that the reach score for your audience in a particular category is higher than the universe it is from, which is a strong signal for you to consider.
An important data card that shares cities you can consider for geo-targeting from the market your audience belongs to. The cities are ranked based on reach score with a max of 100. To visually aid your understanding, a map displays the locations of these cities. A graphical view helps you identify regional concentrations of cities with higher reach scores that can not only help with media planning but also other offline marketing strategies and even logistics. Throughout this report you will come across 3 types of scores: Reach Scores, Uniqueness Scores and Efficiency Scores
Reach Score is a scoring that shows the potential reach of a segment. To make it more understandable this score has been equated to a max score of 100.
Uniqueness Score is a score out of a max limit of 100, for better comparison with Reach Score. This score tells you about the inclination of the segment to the audience selected by the user, in the Omnibox.
Efficiency Score is a composite score of Reach and Uniqueness. This unit is also a measure calculated out of hundred. This score balances out the impact of Reach and Uniqueness and gives you a more balanced scores considering both the values. There can be many other inferences you can draw from this chart, if you look at the data based on your campaign objectives.
This section is a part of the basic report. In this section, you will see two cards: on the left, you will see a colorful tree map, and, on the right, you can see the interests clustered under each theme.
Themes: There are 15 themes that have interest level cohorts stacked in them. Themes help you understand the drift of interests and without them, close to 300 interests bubbled next to each other would just add a lot of data noise, only to overwhelm a user. If you refer to the tree map above, each box is of a different size that is based on Reach Score. The color signifies Uniqueness, starting from dark green (means highest Uniqueness) and goes down to Reddish Orange, that has the least uniqueness value.
Please Note: Lower uniqueness does not mean that it does not contain good interests, these values are relative in nature.
Interests: When you click on a theme, you will be able to see bubbles appear in the card on the right. The way you need to read this 2x2 graph is by means of intersecting values of Reach & Uniqueness scores.
Growth Section: High Reach and Low Uniqueness add up to a growth section. This means interests in them are more suited for Branding and Awareness campaigns.
Ideal Section: High Reach and High Uniqueness would mean that it is ideal for good reach with good uniqueness in the audience, adding up to higher probability of Efficiency.
Niche Section: Low Reach but High Uniqueness would mean that the audiences may be filtered but highly potent. If conversion or lead value is your objective, you might want to look at this quartile.
Ignore Section: As the name suggests, it does not have reach or uniqueness (relative to other interests). If your budgets are limited, you might want to consider other quartiles first before you consider this. It is noteworthy that, since the ranking is relative in nature, it does not mean that an interest in Ignore is bad and tainted forever. It just means that there are better interests right now than the ones in Ignore. A few days later, the same interests from Ignore can also feature in any of the other three.
It is important to note that predicting human behavior is almost impossible. Consumr.ai employs highly sophisticated algorithms to use data to predict the probability of parameters that can work in your favor and make your plans better than any other prediction tools that exist in the market.
Note: This card is a feature of Advanced AI and will not show up in a Standard Report.
This insight is a very interesting piece of data. From a list of hundreds of known brands, consumr.ai picks out the 10 top brands that your audiences are more likely to interact with. This reveals the brand mindset of the consumer. In the screenshot, you can see that this audience's choice of brands is very practical and functional.
The Devices graph shows a simple split between Apple and Android Devices. In a market like the U.S., where audiences are pro IOS devices, a split that shows an almost equal split speaks volumes of the kind of audience you are analyzing. The browser split shows clear dominance of the Chrome browser, followed by Safari.
All four of these charts are shown in comparative bar graphs and are part of the Advanced AI enabled report. Comparative bars charts can be interpreted the same way as the Stages of Life chart. One chart talks about the top five professions your audience dominates and the second shares the household income split in the US. Please note that the income graph is only applicable for the U.S market.
Again, a part of the Advanced AI enabled report, the ‘Observed Traits’ graph shows the habits of the audiences. It is visualized in the comparative bar graph and can be read exactly like the Stages of Life graph. However, the data helps you understand the habits of the consumers that are different from Interests and Themes. For example, in the graph above, you can see that all the habits listed have higher audience scores than the population scores. However, Engaged Shoppers have the highest reach and there is a significant difference in audience and population scores compared to other traits.
This is a different depiction of Audience Reach Score comparison with Population Reach Score. Here while Dancehalls and Coffeehouses are both reaching out to the max limit of 100, Dancehalls shows a significant difference where the audience score is 100 but the population score is at 76. On the other hand, it is clear that the audience we are analyzing prefers Nightclubs lesser than the average population.
When you create a Behavior report, you need to be very clear on the objective you want to achieve and then pick an audience to unpack. Your report will only be as intelligent as the inputs and filters you pick. While reading the report as well, you will need to keep the objective in mind to get the most out of the report.
Feel free to explore the right panel to share, collaborate, see input information, and even delete the report if you don’t want it.
