Where online social learning products are going
“It’s really hard to design products by focus groups. A lot of times, people don’t know what they want until you show it to them.”
— Former Apple CEO Steve Jobs, as quoted in a BusinessWeek article on May 25, 1998.
That’s what inventors do—they make a living looking into a crystal ball and creating products that their customers didn’t even know they needed yet. And after customers experience the first prototype, they become addicted and can’t imagine living without it.
So how are we creating the social learning solution that our customers can’t live without? By focusing on these four areas.
One of our customers told us that a 91-year old lady uses our software. Awesome.
We need to build grandma-friendly software. Why? Because we need to tap into the knowledge of every team member, not just every tech-savvy team member. We never want to hear this complaint again: “It’s not user-friendly. I’m going to avoid the headache and skip using it altogether.” Too many enterprise software solutions get shelved because of this sort of user feedback.
If our customers need help identifying ingredients one and two, we need to be there helping them. And that has little to do with computer programming. We’ve learned that picking up the phone can work wonders. Sometimes, we even do social learning workshops.
When our customers pick Bloomfire, they don’t just pick software. They also pick a team of experienced advisers who will lock arms with you and create success.
Are you fishing for knowledge? Are you asking your team a question using our software? If that’s the case, we know that you want that question answered as soon as possible. You don’t want to wait until people are back at their desks checking in to their social learning environment. That’s why your social learning environment needs to be in your team’s pockets.
That’s part of the reason why our first iPhone app was well-received. Wait until you see version two.
Algorithms are powerful—the BBC News even claims they control the world.
Imagine this. Your smartphone buzzes, and when you glance at it, you notice that someone at your organization is asking a question that you can answer. You type in an answer or use your smartphone’s video camera to record yourself drawing out the answer on a napkin. That question and all answers are now archived and discoverable for now and eternity via search and browse tools.
Here’s what happened behind the scenes.
When your smartphone buzzed, that was because some smart lines of code (an algorithm) calculated that you would be a fitting candidate to answer that question. What were those calculations based on? Data points such as keywords contained in posts that you often read, keywords you’ve used when answering past questions, and much more.
The more you interact with the system, the more the system learns about what you like to learn and what your expertise is. The system can use that knowledge to present questions to candidates who are most likely to provide complete answers, instead of presenting questions to every single candidate. It’s like the system automatically picks and chooses contacts to email instead of spamming everyone in your address book.
If you look at it another way, the algorithm does matchmaking—it matches up people who want knowledge with people who have knowledge.