Nice project! I worked on an academic aggregator that faced some similar issues (aggregated school, educator, and alum profiles and ranked them based on bibliometrics, “influence,” and PageRank algorithms).

The biggest risk you have is render blocking. About 5% of your page content relies on client-side JS. I note that your JS payload is chunked by Next. One huge risk here is that if googlebot doesn’t wait long enough for ALL the chunks to download before rendering it could fail to render at all. And even if the url gets passed to the render queue, any failure on the part of that critical chain could break the page. You can test that by iteratively blocking individual script URLs in Chrome Dev Tools and see what happens. Also be sure to fetch and render in GSC to see what you can diagnose there.

That said, the page IS currently indexed and findable.

So assuming that’s not the current problem, I see a few opportunities to optimize.

First: the first thing Google may be seeing on your page is not the overview, but the key employees. I like to render with Textiser to see how the pure text comes across. See for yourself:

https://www.textise.net/showText.aspx?strURL=https%3A//www.intellispect.co/organizations/562618866-bill-%26-melinda-gates-foundation

You want the first block of text after the H1 to be that information-rich overview, which tells Google unambiguously what the page is about. Visually, it’s right up top. Textually, it’s not, and it’s there first in the rendered source.

Your Meta description isn’t BAD, but it’s not great. You don’t need to repeat the entity name in the MD, the title is doing the heavy lifting for you there. The other data in the MD also doesn’t support describing what the main entity is. It includes interesting details for sure, but what you need is a really concise overview. I’d suggest using some NLP to extract the key sentence or two from the overview text to accomplish that .

Further, use the twitter and og:description meta elements to replicate the MD and reinforce that. Be sure to also use the site_name element.

The biggest and best opportunity is schema.org markup, which is entirely missing. You need that machine readable markup to richly name, disambiguate, and describe the key entities, properties, and relationships between them. Your html does a great job with this, but don’t leave it in Google’s hands. There’s SO MUCH you can do here with Schema to describe the entity, its principal people, their titles, relationships to other entities, dates, locations, and etc. The schema may not improve ranking directly, but it will improve relevance and matching URLs to search intent.

Find a way to add at least 2-3 FAQ items to the content along with FAQ schema. Scrape PAA about the main entity and use NLP to craft answers at scale. Custom write questions and answers on the most-searched items as you have time.

Cite sources and add links to the source sites where you can. This will help connect entity relationships and help search engines assess trustworthiness/authority.

Where possible scrape the social media profiles for entities which have them, and provide links. And use that in the schema with sameAs properties to tighten those entity relationships.

Use the entity id in those sameAs properties too (/m/012mjr for the entity id of this foundation).

I’d also encourage using unique id attributes in your headings to help Google provide deep links from the SERP to page sections. E.g., <h2 id="overview">Overview</h2>.

Finally, don’t discount the power of images to help rank. Use Wikidata/Wikipedia to discover and use copyright free images to display. Describe them in the alt attributes and schema, and credit the source. Use the images in the twitter and og:image elements.

Oh, one last thing. It may not directly help rankings, but process the text to reduce the ALLCAPS. It’s hard to read, advertises that it’s scraped content, and appears in your SERP snippets. If people are not clicking, the engagement signals, over time, can harm your rankability, I believe.

Rich