Search and relevancy are often regarded as simply IT problems, implying that if you install the right software with the right architecture and configuration, your users’ queries will be answered with perfectly ordered and correct results. Obviously it’s not quite that simple — there is a wide range of factors affecting search quality — but in our view, the single most important factor is people.
The concept of the search team is something I’ve written about before, most recently in the free Search Insights 2020 report produced by the Search Network group. An effective search team can help you implement a potentially transformational search strategy; without one your search quality will continue to suffer.
In our Think Like a Relevance Engineer training sessions we introduce a list of Roles in a Search Team:
- Stakeholder — responsible for aligning search improvements with financial and corporate benefit
- Product Owner — responsible for ensuring search improvements meet the information needs of the customer
- Project Manager — responsible for planning and prioritising changes that are translated to features from the customer information needs
- Product Developer — responsible for design and UX implementation in the product
- Content Owner — responsible for defining the content set for the product and coordinating development teams to arrange content access and transport
- Metadata Owner — responsible for defining and managing any metadata assets that are used to improve search, including synonyms, lemmatisation files, spelling dictionaries, word-wheels
- Architect — responsible for integration strategy and planning of technical changes across the system for cross cutting concerns and big-picture technology fit
- Search Relevance Strategist — responsible for solution strategy and planning of technical changes across the system related to search improvements
- Search Relevance Engineer — responsible for search engine tuning and delivering associated measurements and experiments
- Software Engineer — responsible for solution delivery and detail-oriented implementation of functionality and features related to search improvements
- Data Analyst/Scientist — responsible for analytical data access and transport, identifying customer trends and engagement signals, and coordinating judgement and rating data acquisition
We ask our trainees to think about how these roles map to their own organisation and the discussions reveal a lot — especially how mature these organisations are with respect to search & relevance. It’s important to note that only a few of these roles may sit within IT. The ‘perfect’ search team, able to make transformational changes to business effectiveness, maps across many areas of the business, including management, content authoring, customer service and data science.
An organisation that already has a culture of collaboration and that is able to empower cross-functional teams to succeed will fare well in bringing these other departments into the conversation. It’s also important to realise that the search team will need room to experiment, to try various avenues for search improvement, not all of which will succeed. Promoting a strong measurement practice — using metrics that everyone agrees are important — will allow the search team to quickly verify useful approaches and help to avoid blind alleys.
So, once you’ve realised you need to build a better search team, where do you go next? Some of the roles above are simple to understand — a project manager is a well-known quantity — but what about a metadata owner who understands enough about search to be truly effective, or a specialist like a search relevance engineer who knows how to tune your particular technology?
Recruitment is one option, but there is a shortage of good, qualified candidates. Those that do exist will prefer to work on interesting search problems, using cutting edge technologies. They’ll probably be part of the wider search and relevance communities, hanging out at conferences like Haystack, Activate, Berlin Buzzwords or MICES. They’ll be helping to build open source software like Apache Lucene/Solr or Elasticsearch and will keep an eye on academic developments at events like TREC or SIGIR. They might hang out in Relevance Slack.
It’s also important to consider how to train your own staff in search skills — help that Product Owner understand the particular challenges of a search engine project, educate the Customer Service team on how vital the feedback they gather is for ongoing search tuning and teach the content producers how to ‘write for search.’ You should also encourage these people to participate in the events above, watch recorded talks and read widely around the subject. Letting them share their own journey as they learn more about search (by blogging or presenting at a Meetup for example) is another way to publicise how much your organization cares about search — and to attract and retain the best people. Be open with your challenges and discoveries and it will help others in the same position.
Search is a shared problem — and by spreading the load among the search team, you can achieve great results. At OSC our mission is to empower search teams - let us know if we can help build yours.