Similarly, class-action lawsuits often require sign-in through filling in some sort of questionnaire. Previously, these questionnaires would be handled through live phone interview, which is obviously very intensive for both the interviewee and interviewer. The questionnaires are often quite interactive, with different questions being asked dependent on answers to previous questions, or aggregates of previous questions. It would take skilled interviewers a while to learn to interview for any one questionnaire. Qualtrics (and similar survey software) makes this process much, much simpler.
You then also have your regular marketing research, the value of which can be debated... but it is obvious people are willing to pay for the creation and distribution of such questionnaires.
Beyond this, I'm sure there are a bunch of other applications of the software.
This is, in my opinion, the biggest use case for Qualtrics - customer experience research based on surveys or data gathering methods managed from within the platform. You can think of it as Survey Monkey on steroids with some SPSS-lite data analysis functionality built in.
I just recoiled in horror at the thought of my car company asking me to fill out a survey like this and mentally closed the window on it.
The fact that iOS 12 now supports 3rd party apps (==Google Maps) on CarPlay has been a life saver.
First world problems, I guess.
In a world where every other site tries to infer what I like or I want or what they think i want to see on my feed next, or put me in some marketing bucket, it's a breath of fresh air to just be asked what I like or don't like or may be interested in.
I never understood , why would anyone waste their time answering 20+ questions for free?
Why?
* Help products/companies I like to improve
* Help products/companies I dislike to get less bad
* Increase the chances that the product/company will skew towards my preferences
* Hope someone might answer my questions some day (reciprocal altruism)
* Basic decency, helpfulness
* In rare cases, curiosity as to what the questions will be
However, the industry as a whole has been coping with something they call "survey fatigue" which is reflected in a lot of the comments here. There has been a general backslide in survey response rates, though as of a few years ago, it had mostly stabilized around a new normal that was still plenty good for generating excellent data sets to understand the customer experience.
Why do we produce free content for YCombinator? People like to pontificate.
If you want a product to be better how else do you expect it to happen if you don't give feedback? It's certainly better than just waiting and hoping some random improvements appear.
I don't do all surveys or even most but more than 0.
As for customers few companies if any in the world has customer service approaching 'entailing differences in customer perception', most are quite happy to have people wait on phones endlessly or fail to address glaring deficiencies in products or services.
With so much low hanging fruit waiting to be addressed in customer service this obsession with surveys and 'customer experience' seems to be driven by other forces ie continuing obsession with data and metrics by sections of the workforce as panacea and distraction from real changes. But great exit for the brothers, nice targeting, if there is a demand why shouldn't they benefit.
EDIT: And that SAP is not buying the software per se. They're buying the customers and credibility.
You want to build a couple new features. You have 60 person-hours at your disposal. Which one do your users want?
Build two quick prototypes and see which one people actually use more.
You need to convince people to give you money (aka "get customers"). You're not sure what the best way to convince them is. Try 3 different approaches (Landing page with tech details? Youtube ads with customer stories? etc) and see which one works before you spend all of your budget on something nobody uses.
Out of a thousand people walking down the street, only one _might_ be interested in what you do. How do you make sure you focus your efforts on that one person?
Or "we have a million f2p video game players. 99% of them will never spend a dime. 0.1% of them will buy a $100 package once. 0.01% of them will buy a $9.99 package three thousand times. When should we present this package to them? Will we sell more $100 packages if we ALSO have a $200 package? Will we sell more $100 packages to Jane Doe who takes the bus to college at 8:45 AM and plays for 34 minutes 5 days a week?" (obviously that one gets a bit more troublesome)
The above comes with some severe implications re: privacy, filter bubbles, etc. but it's not there for no reason. Though there's plenty of people who just want pretty charts for their own sake; having worked in analytics the toughest question is "we have these charts.. umm... so what now?"
"Once I have these, logging/counting usage is simple. The decision is made with a one-page Excel sheet with the raw numbers."
I think a lot of people would get the data in to excel and not know what to do next. Also, implementing tracking of views, clicks, etc. is non-trivial for a lot of people. Or just a hassle.
Really? In "enterprise" class companies? Managers who can't use Excel like this should be (and probably are) fired quickly and for tracking there are plenty of solutions any junior web developer can implement and report on.
For not spending their time dealing with random excel files being thrown around full of raw figures? It's a common way businesses work but it's an absolute nightmare.
Dashboards mean a bunch of things, one is that people are all seeing the same figures. Another is that people aren't reimplementing the same analysis code (where you can easily get errors, because it's not necessarily going to be obvious how to do the stats on the results). And a very obvious one is the time it takes.
Give me an excel file full of raw numbers and sure, I can pull something together. I can even do it quickly. But I'll bet a boatload of cash I can't do it faster than I can open a link.
I could get another dev to spend the time doing it, but without knowing how much Qualtrics charges it's easy to view this as simply being cheaper.
The first group is worth $1MM, the second $3MM. I think it's likely you'd be able to afford to create both packages, regardless of what time any of your players take the bus.
Mind you I'm not endorsing this approach. But it does make a lot of money.
Often for chips it’s a B2B transaction so you can probably mobilize some of your go-to salespeople or sales engineers and ask them what customers are saying about next gen.
Now what if your customer base were 100x-1000x larger? You might need automated tools to ask your customers what they’re worried about, what issues they have, whether or not they like certain features, what what the relative make-up is of the customer base.
We all know customers don’t always tell reality so this becomes one data point in many in determining product direction.
For every chip you make, you have some expectation of how it will perform, which is its "value proposition."
You want to see if your chips are performing as you predict (fulfilling the value proposition) so you need to interact with a large number of the people whose brains are measuring the true performance of your chips. Since you're dealing with thousands of measurements, you summarize them using math. That's where "stats" come into play. A "metric" is any quantity that is supposed to reflect a measurement, but it usually refers to one specifically designed to be useful. For example, for your chips, the 99th percentile power draw experienced by your users might be a metric you use to guide your design process.
Imagine further that your chips perform differently for different groups of people. Figuring out the best way to divide people into groups to understand how your chips perform is "market segmentation." You probably care about some groups more than others, and depending on how well your chips perform for different groups, you may need to strategically change those priorities over time. That's "targeting."
Meanwhile, different versions of your chips are continually becoming available to people, and you want to detect as soon as possible if a new chip has an unexpected performance regression (or an unexpected improvement!) So you make the latest metrics available in a way that's quickly visually digestible, usually at the expense of all subtlety, but hey, your brain's executive function finds it gratifying. That's a "dashboard."
They have 200+ brands sold over about the same number of markets.
Its useful to provide high level dashboard summarising key metric.
The alternative was some god awful platform without a WYSIWYG editor where you have to code surveys by hand, an enormous waste of time and very inflexible compared to Qualtrics.
Qualtrics basically brings the concepts from that field down into SaaS products and makes them more approachable.
A more typical business is building for a wide variety of people from heterogeneous backgrounds and selling during relatively low-touch encounters. There if you want to know what is going on with customers you need ways to find out and ways to sift the data into useful forms. It's not an easy problem.
I consulted for one company in a consumer-focused service business. They were very energetic users of Net Promoter Score [1] surveys as their default measure. New product? Everybody gets the 1-question survey option after using it. They'd see how that compared to their other products and to competitors. If scores were too low, they'd dig in with other research tools to find out why; new product revisions would be made and measured similarly. It worked very well for them, in that it kept people focused on actual customer experience and not on the HiPPOs [2].
It was such a core part of their culture that they went for related tools internally. When they were changing their software development process, they used NPS scores and other internal surveys to see how it was working for their thousands of developers. To my surprise, I saw the executives taking the numbers very seriously, well aware of the limitations and risks with surveys. I expected to be kinda BS-ish, but I didn't see that at all.
As to your terms:
Value proposition is basically, "What's in this transaction for the customer?"
Customer segmentation is where you notice your customers respond differently to stimuli, so you divide them up into groups. For example, just yesterday we were talking about fancy LED Christmas lights. [3] One customer segment is general-audience consumers who want fancy light displays at the press of a remote. But our customer segment is people who like hacking things, the computer-skilled DIYer. So the value prop for the first segment is something like "make your Christmas tree interesting and different", while the value prop for the second is "this year, hack your Christmas tree!" There are other segments and other key value propositions, which is why there are more kinds of Chrismas lights on the market.
Targeting is just taking particular actions in terms of a particular customer segment. For example, if were making hackable Christmas lights, I wouldn't buy a superbowl ad. I'd use very targeted advertising to reach my computer-skilled DIY market. As well as content marketing, where I'd have somebody write good blog posts about exactly how to hack the lights, so that the posts would end up on HN, Slashdot, Reddit, etc.
Is that helpful?
[1] https://en.wikipedia.org/wiki/Net_Promoter
I guess as companies spend vast amounts to get visibility online (e.g. where Google and Facebook revenue comes from) they need to be able to measure what they are getting for all that money.