With help from SHiNE Content Support, Members First worked on improving their website with automated metadata and structured data to give search services clearer information about its content and organization. The setup keeps ongoing maintenance simple, with just one important responsibility for the member: writing an accurate summary for each page.
Members First, operated by Associated Electric Cooperative, Inc. (AECI), publishes helpful information about energy efficiency, electrical safety, and cooperative membership. Its website already contained a plethora of useful content, but some of the page descriptions or metadata was lacking. SHiNE worked with the member during a one-on-one call and additional working session to strengthen that foundation and prepare the content for modern search and AI discovery to thrive.
Choosing the right information for the site
We started by identifying which metadata and Schema elements fit Members First’s content and publishing structure. Schema is a shared vocabulary that lets a website explicitly describe information in a format search services can process. It can identify a page as an article, name its author, and connect it to the organization responsible for publishing it.
Using Drupal’s Metatag module and Schema add-ons, we configured Article, Organization, WebPage, and WebSite information. This gives services such as Google and Bing additional context about the content they retrieve. The configuration describes Members First as the website and AECI as the organization behind it.
We also discussed other Schema types, including FAQPage, Service, Event, and Person. These can be useful when a site has corresponding content. Selecting the appropriate types is part of the service the SHiNE team provides; the goal is to accurately represent what the website actually offers and what the co-ops business needs reflect.
Automating the ongoing work
Drupal tokens made the solution practical to maintain. Tokens pull values from existing content fields and site settings, allowing metadata to be generated as pages are created or updated. Page titles, images, publication dates, and organizational information can be populated through configuration instead of entered manually and separately on every page by a professional at the co-op.
The only assigned task was to add an accurate summary to each content page. As with all SHiNE sites, a token is provided to use that summary as the description. This keeps the editorial work where it belongs: with the people who know the content. SHiNE handles the technical setup, and the member writes a useful summary without having to edit Schema code.
What changed after implementation
The Heat Pump Water Heaters article provides a concrete example. Its live HTML now contains structured data for the article, organization, webpage, and website. It includes an image, publication and modification dates, and organizational details such as AECI’s website, logo, contact information, and social profiles. The structured data is delivered directly in the page HTML.
The immediate result is a substantial improvement in how explicitly the site describes its content and publishing context. Google documents that Article markup helps it understand article information, while Organization markup helps clarify organizational identity. Bing also supports Schema and JSON-LD to better understand website content.
That stronger foundation matters for AI-powered search, too. Google’s AI Overviews and AI Mode rely on established SEO practices, and Bing’s search infrastructure supports Microsoft Copilot’s web experiences. Structured data provides context that supported services can use as they process the site. Google also identifies Assistant among the properties that can benefit from Article metadata.
The benefits are clearer metadata, more consistent publishing information, and less repetitive work as the site grows. Descriptions become available as the member completes page summaries.
Measuring improvements through Content Support
Our broader Content Support SEO offering helps our members by generating co-op custom reports to identify errors, warnings, and metadata issues, then guide improvements and track progress. In our work with member sites, initial Site Health scores in the 50 to 70 percent range have been improved to as high as 99-100 percent over just a few months of working together.
Capital Electric provides a primary example of those measurable results. Its most current supplied Content Support SEO report shows 99% Site Health across 100 crawled pages, with zero errors and just six remaining low level warnings. Site Health measures technical audit/report findings. Our combined SEO work together resulted in 10 fewer errors and 39 fewer warnings than the earlier comparison report.
A practical starting point through Content Support
Members First’s experience shows how focused technical assistance can improve a website’s search foundation without creating a complicated new publishing process. SHiNE Content Support can help your cooperative review existing metadata, select appropriate Schema, configure automation, and understand what your team needs to maintain to enhance your SEO posture.
For cooperatives interested in AI readiness, a focused review and configuration session offers a practical starting point. The scope depends on your website’s current setup and content. A site with straightforward needs may require only a few hours of support, while additional content work or technical corrections can be remediated with a variety of helpful plan options.
Contact the SHiNE team to discuss AI readiness and SEO services through Content Support. Our team will help identify useful improvements for your site and make them easy for you to maintain moving forward.
Reference links: Members First article • Google Article guidance • Google AI guidance • Bing structured data • Semrush Site Health
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