[Part 2] Measuring the impact of safe and inclusive brand communications
Table of Contents
CXO’s of brands that we engage with are concerned about two aspects of their communications (content, ads, and conversations).
Is our communication safe and inclusive?
This is defined by legal, regulatory, cultural and brand guidelines. Typically this question is relevant during the creation process of the content. In part 1 of our series, we have provided a detailed analysis of how brands can implement solutions and measure the impact. Read more here: https://krita.ai/2022/01/18/inclusion-metrics/
Is our communication published in a context that is suitable and relevant for our brand?
This is driven by brand guidelines and by proactively solving for this enables brands to improve the purchase intent from customers, brand loyalty and relevance. In this Part-2 series, we will cover how brands can implement solutions and measure the impact.
The diagram below describes the impact on a brand by addressing these two questions about their communications:
Definition of suitable, relevant and inclusive content
Suitable Content: “right or appropriate for a particular person, purpose, or situation.” This is identified by a set of rules/criteria that every brand communication should satisfy.
Relevant Content: the quality or state of being closely related to the matter at hand. Relevance is the concept of one topic being connected to another topic in a way that makes it useful to consider the second topic when considering the first
Inclusive Content: content that truly reflects the diverse communities that our companies serve. It means that we are elevating diverse voices and role models, decreasing cultural bias, and leading positive social change through thoughtful and respectful content.
The diagram below describes how answering these questions about the context where a piece of content is published, can get the audience to engage with the brand and take the desired action.
Publishing content in suitable, relevant and inclusive context
Q1) Is the context where my communication is published “Suitable” to our brand?
What is suitable to a brand is defined by the following criteria:
Legal / Regulatory framework of geography.
Brand safety and suitability framework that brands subscribe to follow, example: GARM (global alliance for responsible media).
Cultural context of the targeted audience, and
Brand guidelines that are specific to each brand.
These criteria are converted to a set of rules to map the brand communication to the publishing platform context, prior to publishing. These act as a “exclusion” filter where a brand chooses to not publish a piece of content if it does not satisfy these rules. The diagram below provides a simplified view of how AI technology can answer this question.
There are two metrics brands can use to measure the suitability of the context where the communication is published to the brand:
Cost of errors: This gives a measure of the impact of publishing content in an unsuitable context. The measures include
Cost of errors: The impact in terms of incident management including legal, time, distraction, loss of brand engagement and customers. For example: enterprises spend on an average 7 weeks / year to manage incidents that arise out of incivil/inappropriate/unsuitable communications. Read more here.
Volume of errors: Trends over a period of time on the nature of errors / misses, and
Cost of reviewing content for suitability: This is measured by the effort the organization invests in processes, tools and people to review content as per suitability rules.
Q2) Is the context where my communication is published “Relevant” to our brand?
Given a piece of communication from a brand, customers want to know if it is published in a context that is relevant to that communication. In the digital marketing world, we see companies like Google, LinkedIN etc constantly developing solutions to improve relevance, and hence get a higher bidding / cost of distribution.
Given the variety of communications (messages, ads, job descriptions, blogs, social media posts etc) and the volume of content published, there is a heavy reliance on manual processes to set up the relevance criteria. Also, not all platforms provide the same capabilities. When it comes to internal communications these questions around surfacing relevant content are unaddressed by technology.
Example of relevance:
This is a job advertisement, while it is suitable for the brand, on relevance score (based on context of the geography and the people represented) scores lower.
Whereas, the below advertisement scores higher on relevance:
Relevance impacts uplift in conversion metrics and brand engagement.
Q2) Is the context where my communication is published “Inclusive”?
This is a reflection of what the brand values stand for. Given a piece of brand communication, is it published in a context that represents the brand values of inclusion.
For example: Even if the context where the brand communication is published is suitable and relevant for the brand, it may represent people and demographics not aligned with the brands inclusion goals, like propagating stereotypes, as depicted in the event below. Brands may choose not to engage when such stereotypes are propagated, as seen in the below case.
Inclusion leads to the highest brand loyalty, recall and uplift in conversions, as described in the article by Microsoft below.
How krita.ai can help brands create and publish safe, suitable and inclusive communications
krita.ai is an AI assistant for enabling inclusive and safe content and conversations in enterprises. The diagram below describes how krita.ai integrates into a brand’s content workflows.
Our products answers two questions that brands ask about their content & conversations:
Is our content safe and inclusive as per brand guidelines?
Is our content published in a context that is suitable and representative of the brand?
We are able to analyze text, images and video content to:
Filter content as per brand guidelines, including
Using GARM (global alliance for responsible media): Brand Safety Floor + Suitability Framework.
Detect and flag unconscious bias, toxicity and microaggressions within the content.
Detect suitability, relevance and inclusion of the target where the content is published.
Educate and nudge people about the nature of the issues that need to be addressed.
Recommend fixes to make the content safe, suitable, relevant and inclusive.
This AI assistant is plugged into (or switched on) the most popular enterprise apps where content originates and is distributed. For example: Slack and Salesforce marketing cloud & service cloud.
If you are keen to try out our products for your brand communications, please write to firstname.lastname@example.org