Discover metadata | Kontent.ai Learn

Discovery process

The main idea is to base your metadata around certain foundations. And as highlighted there, you need to at least have an idea about your personas, their journeys, and taxonomies. Only when you understand these aspects, you're able to create a universal content model. Personas, journeys, and taxonomies should be represented within your content model, otherwise, it’s almost impossible to leverage them. Both discovery of personas and mapping their journeys are out of the scope of this course, but we can focus on other general metadata and the taxonomy side of things.

The metadata associated with content needs to work two-way. It should make it possible to select content for the current consumer based on various variables, but it should also help you identify the consumer based on the consumed content. To achieve that, the metadata should help you to answer the questions: Who, What, Why, When, and Where. Let's also add “How” and “How much”, as answering these questions will help you to estimate the effort required in implementing such metadata. This way, you can determine if it makes sense to invest in the creation of such a metadata classification.

To answer these questions, you need to create a set of subtasks or sub-questions. For example, specifying personas can be a lengthy process that involves several steps and a multitude of variables. These subtasks are project-specific, but we can identify some basic guidelines.

Google’s approach to metadata

The following is an interesting approach suggested by Google. Google recognizes “well advised”, “right here”, and “right now” consumers.

A “well advised” user is a research-based consumer, so you need to cater to them with your user journeys and content strategy.
The “right here” consumer can be supported with location metadata.
The “right now” consumer should be allowed to proceed with the service, content access, or purchase immediately, and what’s most important, this consumer journey needs to be device independent.

Generally, your metadata needs to reflect the user’s intents. In order to identify your user’s intents, check search logs, Google Analytics, or user behavior on your website.

Common metadata

The following questions will help you to come up with appropriate metadata categories.

Who are your users?

One of the basic metadata categories should be the persona that the current content is suitable for. You need to understand your personas and their goals, and then see how you can fit in value-add in a way that advances your goals. That’s why it is crucial to make persona-specific content and have metadata supporting it as well. If you have only one metadata category, it should be this one. Know that if you decide to implement your persona metadata this way, content can’t be easily recategorized. It's possible, but it requires going through all content and re-assigning the correct persona. An alternative approach (flexible but also more complex) is covered further down. Example metadata category: Persona [B2B, B2C, etc.]

What content would best support your users?

This area is out of the scope of this course, but if you have sufficient resources, make sure the content is approached like any other project. Put your content and all of its components through a research phase, architectural design, beta development, testing, optimization, and launch phases. This order can be reflected via your workflows, where you can have workflow steps corresponding to these content crafting phases.

When should the content be displayed?

You need to define rules that will tell your system when displaying the given content is relevant. These rules then help you identify required metadata in order for the rules to be enforced. You can think of this question in the context of your consumer journey phase, actual time, or if the context is right, for example, an article about “How to keep warm” if it’s freezing outside. These kinds of rules usually come into play in the later phases of your marketing strategy, as they require a lot of planning and nearly flawless execution. Example metadata category: Time of day [Morning, Noon, Evening, etc.], Consumer journey stage [New, Returning, Customer, etc.], Weather [Sunny, Rainy, Hot, Cold, etc.]

Where will you display it?

Your content across all channels needs to be consistent. However, it needs to adapt for a specific channel. Channels and their possible connection points can be identified on your customer journey maps. This bridging of channels experience will create one of the possible “wow” moments for your consumers, which is what you want to achieve as often as possible. Even though you might need to adjust content for specific channels, you need to keep the models as generic as possible. If you start creating channel-specific content, you end up with redundant content. For example, don’t focus on specific social media channels, but use one content model for all the social networks, if possible. Example metadata category: Channels [Social media, Web, Voice, Embedded content, Podcast, Review sites, TV, Radio, Slideshare, Blogs, etc.]

Why are you displaying/creating this?

Does the content align with your goals and those of your content consumers? You need to be able to determine if the content is relevant to the consumer. The content will be consumed only if it is relevant. This relevancy is tied in with customer intents, which can be represented as metadata. You can think of this question in the context of your consumer journey phase. For example, what is the customer currently cautious about in the current journey step? If it’s maintenance instructions for a car, your users may want to know how often scheduled maintenance needs to be done for different components, how to lubricate, replace, or inspect different components, and so on. Of course, the classification can be more complicated and have intents nested into each other or have all kinds of relationships between each other. For each intent, you also define parameters that you need to know to find the most relevant information. For example, if the intent is “lubrication”, you need to know at least the name of the component to be lubricated. Once you know what users may ask and what you have in your content, you need your content to be tagged with metadata that specifies whether this piece of information is about scheduled or unscheduled maintenance, lubrication, inspection, or replacing the component, what component it describes, and so on. The process of assigning metadata can be completely manual or automated with some human supervision. Kontent.ai can support both approaches. That is, you can always manually add metadata, but you can ask the metadata engine to automatically analyze the text (by using various natural language processing algorithms) and add metadata for you automatically (which you can always edit). Example metadata category: Company Goal [Product promotion, Service introduction, Brand awareness, Thought leadership, etc.], Consumer goal [Increasing effectivity, Saving money, Simplifying daily tasks, Increasing ROI, etc.], Buying stage [Seeing a product, Thinking of buying it, Buying it, Post-purchase care]

How will the tagging be achieved?

Not all metadata is entered the same way. Some metadata requires a checkbox or drop-down selection, others require editors to write up a summary of the just written up text. Make sure the process is as simple as possible and consider using automation techniques, such as AI auto-tagging or auto-generated summaries for specific channels, e.g., voice-description. This logic or auto-generated content can be implemented on the channel front end instead of in the content model if the reuse of such content is not possible.

How much effort will it take to get it implemented?

This is one of the questions that is sometimes not considered at all. Make sure the content model you are designing won’t break your budget. There can be, certainly, metadata overlap, so strive to identify this overlap as soon as possible to reduce the amount of required work. In order to achieve this, create a metadata relationship diagram and identify any 1:1 relationships. For example, if you consider having metadata for personas and their goals separately, check if each persona doesn’t have only one unique goal. If that’s the case, the persona metadata classification is sufficient, as it overlaps with the goals taxonomy. Also, think about the long-term and the possibility of changing requirements. The metadata model you specify should be easily extensible and replaceable. If possible, avoid complex classification and focus on the essential metadata which will help achieve your goals. Think in terms of an MVP (minimum viable product) where 20% of the functionality will give 80% of the value for you and your customer.

Metadata selection criteria

When designing your content models, focus on the most important metadata first. The difficult part is to identify which are your most important metadata categories. You may have come up with a long list of metadata categories on your workshops via free listing

or similar activities. Now you need to narrow these lists down. This can’t be answered generally for all industries, companies, or projects, but you can be guided by the following questions:

Does the metadata category support the two-way identification of content and content consumer?
Does the metadata support answering any of the relevant five Ws?
Is the implementation of such metadata feasible?

You can create a similar looking table as below by answering these questions. You should be able to get at least one “Yes” in all columns of this table. If there is an overlap, pick the metadata with the least implementation and entry effort.