When SEO meets the MVP process on Bashfully

This is part of a series about my side project Bashfully, which aims to give graduates and other new entrants to careers a seasoned professional level way of expressing themselves through the super power of story telling. Following the core principles of being discoverable, personalised and guiding in approach.

 So after getting the SEO infrastructure sorted out we are back into an experiment and observe phase. 
LinkedIn on Google
 LinkedIn is the yard stick that we need to beat. The features that we are honing in on based on the MVP process are discoverability, customisation, and guidance. These allow us to add value as a David fighting the awesome network effect of the LinkedIn's Goliath. As an example to the left is a search result for me going to my LinkedIn profile. There are a couple of points that I like - my name, job title, location, and current employer are all easy to read. The thing that I don't like is that the description is very impersonal. Is the fact that I have had 7 roles really the most interesting thing about me? Or is it doing more to tell LinkedIn's story? Is this their SEO not mine?

 I'm not just picking on LinkedIn here, it is the best out of the other profiles that I have. AngelList, GitHub, and Flickr are all very fact-and-figures based. 
Bashfully on Google
Now a look at the Bashfully results. Taking the LinkedIn good points, this needs the current role. But I think that we have done a good job in the content organisation and meta data to put the story front and center. This puts something of my story and aspirations right there. With my current role and employer I think it will round it off nicely.

 One of the problems in testing this is that Google is very much a black box. You can't tell them how to display things, you have to give them hints and hope that they take them. It's actually very much like being a Product Manager, working with influence and not direct authority.

 The main thing that we started testing this week was the rich data structure to help pull together a profile owner's digital footprint. Unfortunately, the Google Search Console doesn't report on the rich data for people or organisations. There is a "jobs" type but it has required fields that we don't, or want, the data for.

 The lesson to learn from this is to get the basics right. Structure your pages so that Google picks out important content. Then use CSS to visually represent this to your uses. Next you can build on hinting to Google and crafting search result snippets.
Edit2: Second lesson was that the Google Structured Data Testing Tool doesn't flag all the errors that the Google Search Console does. Somewhere in some refactoring of the solution, as we learned from what we needed and the results started appear, the "name" got lost. This was quite an important bit of metadata to not be there! So, even if you think that you have got it right, test the live site and watch the results separately. 

 Edit3: Third lesson. We accidentally introduced a "duplicate" page in terms of content - but with a different layout - and it started to get preferred in results over the main page that was in sitemap.xml. So we have started adding in link rel="canonical" in page properties to give Google a further hint.

Other search engines

So far we have been very Google focused, and had some success. Now it's time to move onto other engines. We are starting with Bing and DuckDuckGo (which uses Bing as part of its ranking/indexing system). Bing actually has quite a nicer result for LinkedIn than Google. They support a similar range of markup that we already have on the site, including Open Graph and Schema.org.
Bing example search result

 On the other hand DuckDuckGo has security as its main feature, so the results are rather sparse. It is a nice touch to put the sites logo alongside the URL though.
DuckDuckGo example search result
Edit1: As a minor success after registering with Bing webmaster tools, I have managed to get Bashfully to appear on the first page for some key search terms! This is mainly seems to be down to the OpenGraph data and structure/content being relevant ... but not the individual profile pages yet

Further reading


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