Show HN: Product Substitutes – what software top companies are replacing

Okay. That addresses one update; how about the main focus of my comment, the thousands of low-value tweets that @ mention companies and people?

A great use case where we can increase the granularity of categorization/tagging and potentially separate the infrastructure provider and the implementation layer on top of it.

What we're doing with Substitutes is to complement the NPS ranking with a mapping of actual switch behavior. It's entirely possible that a lower-rated product is a much more popular substitute for a product if it's a better fit (e.g. targeting SMBs or Enterprise).

An example: In the Recruiting/ATS space, Greenhouse and Lever are each other’s most significant competitor. Meanwhile, companies looking to replace iCIMS by far most frequently end up using Oracle Taleo (and vice versa)

We generally see company size and employee count is highly predictive of which products they’ll consider and we can see a progression as companies grow out of services catering to SMBs to more fully-featured alternatives.

Source of data:

0) We analyze products that have a public footprint.

1) We analyze products that don't have a public footprint.

2) For 0), we crawl the internet periodically and create a time series curves of B2B product usage for companies.

3) For both 0) and 1), our verified community has trained our algorithms with tens of thousands of data points on usage and sentiment, thereby reinforcing or nullifying these deductions.

4) If you have stopped using Angular and started using React (or vice-versa now that Angular 5 has better server-side rendering), it is deductible at a global context.

Yeah, NPS is a good way to understand how actual customers feel about a product. We have collected tens of thousands of sentiment over the last six months on a wide range of products, and at scale, this sentiment data set can be quite valuable.

Yes I found the wikipedia page later but it was confusing the first time around. The second data point on customers is intuitive though.

I just wish there was a "what is this?" explanation somewhere. Maybe a hover over text like the one showing - promoters vs detractors.

Yeah, we decided to de-clutter the LP (would you say we overdid it?), but the About Us link is on close to 1M pages throughout the site. Not hiding :) https://siftery.com/about-us

Agree, need more granularity than just "Javascript MVC framework". Thank you, we are on it.

In this case, the primary category for Intercom is `User onboarding and Engagement` which can be broken down separately to `User Onboarding` and `In-app Support` or `In-app Chat`. That will suddenly spike up the sanity of both categories (maybe we can even normalize further - siftery has more than 700 categories/tags, a first for any such platform).

Categorisation of a data set like this can be non-trivial and will false positives. We can cherry-pick such a false positive and ignore all the actual positives. That said, thanks for this feedback - this is exactly what is needed to improve status quo. We are on it and will report back in a few hours with the category split I suggested in the previous paragraph. Do let me know if you think it can be broken down into a different type of granularity?

We use Intercom quite a lot at Siftery. What would you say are the top alternatives/substitutes if not what's listed?

Here's what we have for the "substitues" calculation: "When companies stop using Intercom, its most frequent substitutes are Drift (44.9% of the time), followed by Zendesk (9%), and by Zendesk Chat (Formerly Zopim) (7%)"

(Drift as the closest substitute closely matches my experience investigating options in this space; other products are more like partial or imperfect substitutes)

The alternatives ranked by NPS include Appcues, Chameleon, Clickhelp, Tawk.to, Olark, Freshdesk. Intercom is multi-faceted and difficult product to categorize, but all of those products are alternatives for some of its functionality.

Are there other products you think definitely belong here and were missed? Not trying to come off as defensive by the way, just trying to really understand where's the opportunity for improvement here.

How about not emailing like that from the start without an opt-in?

Google mines that data by other people searching for that, not (only) by scraping it off sites. Yes, they also do that, but AFAIK search trends have a higher relevance than scraped suggestions.

As long as people want to know how their existing product stacks up against another product they have heard of before, "<existing product> vs <other products>", will be searched and appear in the autocomplete.

This approach breaks down tough for newer products, ot if you want to find the best product by quality, not just popularity.