I spoke at, and attended, the Content Strategy Applied 2017 conference last week. One of the keynote speakers, James Mathewson, provided a fascinating description of how IBM uses audience intent modelling to map its content plans. By doing this IBM is able to align its content with the buying cycles for their target personas.
This planning involves the management of 300 million pages and 100,000 marketing assets, and they use a dizzying array of artificial intelligence and software to improve their search engine rankings. However, their strategy is actually very simple.
There are three forms of audience intent
These are informational (learn about a topic), navigational (find information about a topic), and transactional (find a place to buy the solution or get help).
There are two kinds of audience
These are business people and specialists.
There are two kinds of queries
These are branded and unbranded. Most searches are unbranded questions, and people only move to branded questions when they are ready.
There are five stages in the IBM customer journey
Here are the steps and the type of content IBM provides:
- Discover – What is big data? web page
- Learn – Video on big data (“Four ways big data and analytics transform marketing”)
- Solve – A product information page (“14 top big data analytics platforms”)
- Try – The offer (Watson Analytics 30 day free trial)
- Buy – A whitepaper (“Understanding Watson Analytics”)
IBM has invested heavily in technology
This is used to maintain consistency in the tagging of content, and in the tone and voice. It’s also used to learn what audience want, and are searching for on the web. A lot of searches are in the form of questions, so they mine those questions to discover what they are asking.
IBM avoids online marketing tricks
James said “clever messages to push people and trick them” rarely work online, and if they do the reader is unlikely to come back. Instead they focus on what the audience wants, and aim to meet that need.
It was the best presentation at the conference, and it provided lots of ideas for Cherryleaf’s website.
I spoke at, and attended, the Content Strategy Applied 2017 conference last week. One of the keynote speakers, Madi Weland Solomon, explored what the impact of content has on users, and the trends that will inform content strategy in the near future.
She said one of the key challenges for organisations will be dealing with the loss of trust in information. She quoted a survey that stated over 50% of Americans have no trust in mainstream news. Her suggestions to fix this was to become more active at representing the public (and end users). Organisations should use more human-centric data and focus on helping users. Referring back to Dale Carnegie, Madi said being useful, and being seen to be an advocate for users, was vital. She suggested the law of reciprocity would play a part in users returning the favour of being helped by the company.
Help and other forms of user assistance meets this type of need. It is already seen at some of the most trustworthy content on the web, and it is useful. The should not be hidden about behind a firewall, but helping to build and sustain the trust between the organisation and the their users.
She also looked at which type of content is read the most: blog articles that have roughly a seven minute reading time. This fact is more problematic for technical communicators, as the trend is to write short chunks of information. Perhaps there is a need to rethink this style, in some situations.
One of the trends in both data and content management is the move away from silos. In data management circles, there is a trend towards the collection and aggregation of customer data into “data lakes”. According to Margaret Rouse, a data lake is:
A storage repository that holds a vast amount of raw data in its native format until it is needed. While a hierarchical data warehouse stores data in files or folders, a data lake uses a flat architecture to store data. Each data element in a lake is assigned a unique identifier and tagged with a set of extended metadata tags. When a business question arises, the data lake can be queried for relevant data, and that smaller set of data can then be analyzed to help answer the question…Like big data, the term data lake is sometimes disparaged as being simply a marketing label for a product that supports Hadoop. Increasingly, however, the term is being accepted as a way to describe any large data pool in which the schema and data requirements are not defined until the data is queried.
(source: what is a data lake?)
“Content lake” isn’t a word that’s used in the content management or technical communication sectors yet, and whilst it seems unlikely end user content will grow at the same rate as other forms of data, there’s a fair chance this phrase could catch on.
A content lake is likely to have similar attributes to a data lake:
- Content will be stored in a native format that is then changed into other formats.
- It will use a flat architecture to store data.
- Content will be stored in some type of structured format. Perhaps XML, JSON or plain text (with AsciiDoc-like attributes assigned to certain sections). However, user documentation does not require the rigorous structure of other forms of content.
- The content lake can be queried for relevant content, and that a smaller set of information can then be extracted to help answer questions. This might not mean publishing content on-the-fly, but generating PDFs, CHM files and web-based content from a single source.
- Rather than content being simply archived, it will deliver the right information in very short timeframes.
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At the TCUK 2015 conference, Rachel Johnston mentioned the idea of a content maturity model. We thought we’d take this idea and ask:
Could we develop a model that illustrates a hierarchy of needs for users of technical communication (and in particular, User Assistance)?
A model of what?
We suggest calling this model a technical communication user’s hierarchy of needs. This is because we’re considering the different points where a user interacts with technical communication content, the information they need, and value it gives to them.
It takes a similar approach to the content maturity model Rachel suggested (shown in the photo below), with the least mature organisations providing just the legal minimum, and most mature content systems contributing to branding and evangelism.
A user’s hierarchy of needs also enables us to compare this model to similar models from content marketing and product design. For example, the categories in our model’s hierarchy roughly correspond to Peter Morville’s “User Experience honeycomb”, as well as the key elements in product design.
Continue reading “A technical communication user’s hierarchy of needs”
I was one of the presenters at last week’s Technical Communication UK 2015 (TCUK) conference. TCUK is the Institute of Scientific and Technical Communicators’ (ISTC’s) annual conference for everyone involved in writing, editing, illustrating, delivering and publishing technical information. It’s an opportunity for Technical Communicators from the UK and mainland Europe to meet up and mingle, learn and present.
Here are my reflections on the event.
Continue reading “Reflections on the TCUK15 conference”
I was asked to take part in the ContentHug series of interviews on technical communication and content strategy.
It was fun and challenging, going through the questions.
ContentHug’s Vinish Garg is interviewing a number of consultants involved in technical communication and content strategy, and asking them essentially the same questions. By reading the interviews, you can see where there are areas of agreement and where there are a variety of opinions. In general, there is a fair bit of consensus. They are worth reading.