Data-driven decisions with Net Promoter Score

Today we’re releasing some changes in the way users sign up for Impactstory profiles, based on research we’ve done to learn more about our users. It’s a great opportunity to share a little about what we learned, and to describe the process we used to do this research–both to add some transparency around our decision making, and to maybe help folks looking to do the same sorts of things. There’s lots to share, so let’s get to it:

Meet the Net Promoter Score

As part of our journey to find product-market fit for the Impactstory webapp, we’ve become big fans of the Net Proscreen-shot-2016-09-15-at-7-26-10-pmmoter Score (NPS), an increasingly popular way to assess how much value users are getting from one’s product. It’s appealingly simple: we ask users to rank how likely they’d be to recommend Impactstory to a colleague, on a scale of 1-10, and why. Answers of 9-10 are Promoters, from 1-6 are Detractors. You subtract %detractors from %supporters and there’s your score.

It’s a useful score. It doesn’t measure how much users like you. It doesn’t measure how much they generally support the idea of what you’re doing. It measures how much you are solving real problems for real users, right now. Solving those problems so well that users will put their own reputation on the line and sing your praises to their friends.

Until we’re doing that, we don’t have product-market fit, we aren’t truly making something people want, and we don’t have a sustainable business. Same as any startup.

As a nonprofit, we’ve got lots of people who support what we’re doing and (correctly!) see that we’re solving a huge problem for academia as a whole. So they’ve got lots of good things to say to us. Which: yay. That’s fuel and we love it. But it can disguise the fact that we may not be solving their personal problems. We need to get at that signal, to help us find that all-important product-market fit.

Getting the data

We used to manage creating, sending, and collecting emails surveys. It just works and it saved us a ton of time. We recommend it.  Our response rate was 28%, which is we figure pretty good for asking help via email from people who don’t know you or owe you anything, and without pestering them with any reminders. We sliced and diced users along many dimensions but they all had about the same response rate, which improves robustness of the findings. Since we assume users who have no altmetrics will hate the app, we only sent surveys to users with relatively complete profiles (at least three Impactstory badges).

Once we had responses, we followed up using Intercom, an app that nicely integrates most of our customer communication (feedback, support, etc). We got lots more qualitative feedback this way.

Once we had all our data, we exported the results into a spreadsheet and had us some Pivot Table Fun Time. Here’s the raw data in Google Docs (with identifying attributes removed to protect privacy) in case you’d like to dive into the data yourself.

Finally, we exported loads of user data from our Postgres app database hosted on Heroku. All that got added into the spreadsheet and pivot tables as well.

Here’s what we found

The overall NPS is 26, which is not amazing. But it is good. And encouragingly, it’s much better than we got when we surveyed users about our old, non-free version in March. Getting better is a good sign. We’ll take it.

Users who have made profiles in both versions (new and old) seem to agree. The overall NPS for these users was 58, which is quite strong. In fact, users of the old version were the group with the highest NPS overall in this survey. Since we made a lot of changes in the new app from the old, this wouldn’t have to have been true. It made us happy.

But we wanted more actionable results. So we sliced and diced everyone into subgroups along several dimensions, looking for features that can predict extra-high NPS in future sign-ups.

We found four of these predictive features. As it happens, each predictor changes the NPS of its group by the same amount: your NPS (on average) goes from 15 (ok) to 35 (good) if you

  1. have a Twitter account,
  2. have more than 20 online mentions of some kind (Tweets, Wikipedia, Pinterest, whatever) pointing to your publications,
  3. have made more than 55% of your publications green or gold open access, or
  4. have been awarded more than 6 Impactstory badges.

Of these, (4) is not super useful since it covaries a lot with numbers of mentions (2) and OA percentage (3); after all, we give out badges for both those things. A bit more surprisingly, users who have Twitter are likely to have more mentions per product, and less likely to have blank profiles, meaning Feature 1 accounts for some of the variance in Feature 2. So simply having a Twitter account is one of our best signals that you’ll love Impactstory.

Surprisingly, having a well-stocked ORCID profile with lots of your works in it doesn’t seem to predict a higher NPS score at all. This was unexpected because we figured the kind of scholcomm enthusiasts who keep their ORCID records scrupulously up-to-date would be more likely to dig the kind of thing we’re doing with Impactstory. Plus they’d have an easier and faster time setting up a profile since their data is super easy for us to import. Good to have the data.

About 60% of response included qualitative feedback. Analysing these, we found three themes:

  • It should include citations. Makes sense users would want this, given that citations are the currency of academia and all. Alas they ain’t gonna get it, not till someone comes out with a open and complete citation database. Our challenge is to help users be less bummed about this, hopefully be positioning Impactstory as a complement to indexes like Google Scholar rather than a competitor.
  • It’s pretty. That’s good to hear, especially since we want folks to share their profiles, make them part of their online identity. That’s way easier if you think it looks sharp.
  • It’s easy. Also great to hear, because the last version was not very easy, mostly as a result of feature bloat. It hurt to lose some features on this version, so it’s good to see the payoff was there.
  • It puts everything all in one place.  Presumably users were going to multiple places to gather all the altmetrics data that Impactstory puts in one spot. 

Here’s what we did

The most powerful takeway from all this was that users who have Twitter get more out of Impactstory and like it more. And that makes sense…scholars with Twitter are more likely be into this whole social media thing, and (in our experience talking with lots of researchers) more ready to believe altmetrics could be a useful tool.

So, we’ll redouble our focus on these users.

The way we’re doing that concretely right away is by changing the signup wizard to start with a “signup with Twitter” button. That’s a big deal because it means you’ll need a Twitter account to sign up, and therefore excludes some potential users. That’s a bummer.

But it’s excluding users who, statistically, are among the least likely to love the app. And it’s making it easier to sign up for the users that are loving Impactstory the most, and most keen to recommend us. That means better word of mouth, a better viral coefficient, and a chance to test a promising hypothesis for achieving product-market fit.

We’re also going to be looking at adding more Twitter-specific features like analysing users’ tweeted content and follower lists. More on that later.

To take advantage of our open-access predictor, we’ll be working hard to reach out to the open access community…we’re already having great informal talks with folks at SPARC and with the OA Button, and are reaching out in other ways as well. More on that later, too.

We’re excited about this approach to user-driven development. It’s something we’ve always valued, but often had a tough time implementing because it has seemed a bit daunting. And honestly, it is a bit daunting. It took a ton of time, and it takes a surprising amount of mental energy to be open-minded in a way that makes the feedback actionable. But overall we’re really pleased with the process, and we’re going to be doing it more, along with these kinds of blog posts to improve the transparency decision-making. Looking forward to hearing your thoughts!

Who’s the tweetedest?

Formal citations are important, but it’s the informal interactions that really power the scientific conversation. Impactstory helps our users observe these. And since Monday, they’ve been able to observe them a lot more clearly: adding Twitter data from has significantly improved our coverage, to the point where we’re confident saying Impactstory is most comprehensive source of scholar-level Twitter data in the world.

We wanted to play with all this data a little, so we thought it’d be fun to find the three most tweeted scholars on Impactstory.  Congrats to Ethan White, Ruibang Luo, and Brian Nosek: y’all are the Most Tweeted, with nearly 1000 tweets each mentioning your research papers, preprints, and datasets!

But of course, while these numbers are impressive they’re far from the whole story. By diving into the content of individual tweets, we can learn a lot more.

For instance, Ethan posted a grant proposal on figshare. This isn’t a traditional paper; it’s not even cited (yet). It’s not helping Ethan’s h-index. But it is making an impact, and looking at Twitter can help us see how. Zooming in, we can find this take from @ATredennick, a PhD candidate in ecology at Colorado State:

Thanks @ethanwhite for posting successful NSF proposal, . Very useful for early-career scientists.

That’s one tweet; there are 53 others for this product. Now we’re looking beyond simple counts and starting to tell data-driven stories–stories we’d never see otherwise.

Right now we’re only linking to a subset of tweets for each product, but we’re working to add the ability to see all of ‘em. We’re also going to be bringing data about tweet locations and authors (are you being tweeted by a fellow scientist? a blogger? your labmates?) right into your profile. If you’ve got other ideas for Twitter features, let us know!

In the meantime: congrats again to Brian, Ruibang, and Ethan! We’ll be sending them each a swag bag with an Impactstory “I am more than my h-index” tshirt, and stickers featuring our new logo.

Want to find who’s tweeting your science? Make your profile to find out!