Previously, we’ve looked at the challenges that Erin, Lisa, and Marta face on their quest to deliver high-quality, effective multilingual content for Healthsoft, Inc. Today, we explore how a designer mindset can help overcome some of those challenges, and outline specific steps to make your global content quality management program truly customer-centric.
Some of the tools in a traditional designer’s toolkit
Content as Design: User Needs vs Business Needs
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Have you ever thought about the difference between design and art, or designers and artists? It seems that many people often confuse the two. Yet there’s a very strong, fundamental divide between them:
Designers solve problems. Artists express their personalities.
The same perspective can be easily applied to content creation and localization. In a commercial setting, content is rarely, if ever, commissioned just for the sake of unleashing the creative spirit of its authors, reviewers, translators, and all other people that collaborate to publish it. Ideally, each piece of content (be it a caption for a button in the mobile app UI, a video ad on TV, a technical manual, a landing page on a website, or a legal contract) has behind it a specific purpose and serves a specific need.
Now, designers know very well that there are two types of needs: those of the people who will use the product, and those of the company that will create and sell the product. They work very hard to balance user needs and business needs when solving design problems. No design can be considered “good” unless it is able to reach and maintain this (often fragile) balance. To make this balancing act easier, specific design criteria are established to evaluate the quality of each design in a more objective fashion and guide subsequent iterations.
While design criteria may include a number of different things, they are usually NOT focused purely on aesthetics. Instead, designers ask themselves (and the people around them): “Does my design solve the users’ problem in a way that’s viable and feasible for the business?” Granted, there’s always a lot of room for self-expression and personality to shine through. However, those factors are rarely the key criterion that distinguishes “high-quality design” from “low-quality design”. After all, that’s exactly why design is not art.
Contrasting Monolingual and Bilingual Worlds
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Let’s now venture back from the world of design to the world of digital content, specifically multilingual global content. What do we see?
First, let’s check out those parts of the global content supply chain that are mostly working in a monolingual context: content marketers, copywriters, technical communicators, instructional designers, and — partially — user experience designers.
Their processes seem to be pretty well aligned with the notion of “quality as effectiveness”, as found in the world of design.
They are usually quite proficient at measuring the impact of their content on the readers by using outcome-based KPIs as primary quality metrics.
These quality metrics often include campaign conversions, clickthrough rates, learning effectiveness, problem resolution rates, user scenario completion/error rates, and customer satisfaction.
However, they are rarely concerned about how their content performs in another language or culture. And even if they are, they wouldn’t understand how to improve its bad performance or how to capitalize upon good performance.
Now, let’s take a look at those parts of the global supply chain that are mostly working in a bilingual context: translators, localization managers, translation quality managers, in-country reviewers, software localization testers, etc.
Their processes seem to assume (and of course, I’m oversimplifying here): if source content is high quality and we faithfully replicate that content in another language, then translated content is also going to be high quality.
They usually approach this by implementing translation-level quality metrics (for example, around language rules, terminology, or accuracy) and arranging the processes to measure and improve them.
They know very well how to make their multilingual content better. However, they are rarely concerned by how these metrics actually correlate with meaningful business outcomes driven by this content.
To me, this situation with dual views of quality in the global content supply chain is a bit like a two-headed monster (and no, I don’t mean the one from the Muppets). Each head is looking in its own direction, and they are not talking to each other. Each head is trying to pull the body to one side, and as a result, nobody gets anywhere.
7 Steps to Make The Most of Content Quality Metrics
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I think it’s about time we help the two monster’s heads start talking to each other. Or, if you wish, arrange a strategic marriage between members of those two slightly hostile factions. Here’s one way how this could be done:
1. Remember that all business content, whatever the language, is created for a purpose.
If this purpose is not being fulfilled, it means that content is likely low quality — regardless of what translation metrics might say.
However, if this purpose is met, on the other hand, then the quality is at least good enough.
Whether to improve quality further or not is a separate decision and requires extra analysis.
2. Use the same set of customer-focused, outcome-based KPIs as the final, highest level measure of content quality in ALL languages (= not just for your source language).
Keep in mind that different content types have different customer-centric quality (or effectiveness) metrics. What would work for an email campaign might not work for an e-learning course.
Often these would be lagging metrics. That is, you won’t get good data until after you publish the content.
Comparing this data across languages will enable you to pinpoint the weakest and the strongest performing locales in your global content strategy, and help focus your improvement efforts.
3. For each language (including your source language), collect interim content quality KPIs of different types, levels, and from different data sources.
Many of these are leading metrics — you can get them before you make the content publicly available.
There are many examples of such metrics and evaluation approaches: human and machine, holistic and atomistic, review-based and testing-based, bilingual or monolingual, etc.
Typically, global content programs have a mix of different content quality data sources within relatively easy reach.
4. Correlate interim metrics with final metrics for the equivalent content and language.
This will uncover patterns and provide insights for further deep analysis.
However, be careful: correlation (the fact that 2 metrics have similar trends) doesn’t always mean causation (the fact that one metric directly influences the other)
5. For selected languages, perform root cause analysis to identify the factors that affect final metrics most strongly.
Remember to look both at positive influence (drivers) and negative influence (inhibitors).
6. Rearrange authoring & localization processes to leverage drivers and negate inhibitors.
Careful, controlled changes are key to make sure that no external forces can distort the outcome.
7. Evaluate the results via final metrics and plan the next experiment accordingly.
The quest to deliver higher quality global content for less investment never ends.
Using the right tools for the job helps make the process easier, but, as with any other complex process, it needs people to be effective and efficient.
How does the content quality management process work across languages in your organization, and how do you enable its continuous improvement? Please share in the comments.
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