How SurveyMonkey can Leverage Emerging Technologies to Grow and Innovate

SurveyMonkey was started by brothers Ryan and Chris Finely as a 12 person Silicon Valley startup in 1999. Since then, it has grown to acquire several companies including TechValidate, Usabilla and Zoomerang. It was named to Forbes’ Unicorn list of startup companies in 2015 and was 13th on Forbes’ Cloud list in 2018.

Here are 5 ways SurveyMonkey can leverage emerging technologies to further grow and innovate in the future

1) Machine Learning

SurveyMonkey has recently integrated Artificial Intelligence into their software for the purpose of developing survey questions tailored to the user based on their past responses. They can further leverage this technology — specifically machine learning — to make predictions and draw generalizations based on the data that a client ammasses.

Often times, humans are incapable of noticing the correlation between two variables because they are seemingly independent or their relationship is counterintuitive. For clients working in any social domain, missing such an association will hinder the progression of their work, and prevent it from realizing it’s full potential.

With the power of machine learning, a SurveyMonkey computer can efficiently “learn” the client’s collected data and return a generalization or set of predictions. The client can then walk away with something they can directly apply to their work rather than a set of data they would have to analyze to obtain the same result.

2) Quantum Computing

Let’s say that SurveyMonkey was using machine learning on a client’s data, but doing so would not be instantaneous due to the dataset’s size. This would detract from the client’s experience. Using Quantum Computing, SurveyMonkey can vastly speed up their computation time, effectively abolishing this delay.

3) Internet of Things

What if a client wants to use the data they collect to better program a “thing” — be it an HVAC system or a water filtration device? Well, instead of the client manually programming the item given what they learn, after using machine learning on the data to produce a decision, SurveyMonkey can leverage the Internet of Things (IoT) to automatically load the decision into the workings of the object. This saves time, and effort on the client’s part and reduces the chance for human induced error.

Plus, if the survey stays live and users continue to input their data, then the neural network can be continuously learning. The device can adjust to reflect changing preferences as they come up, rather than the client continuously having to make adjustments themselves.

4) Edge Computing

Continuing in the vein of using a machine learning decision to influence a device, rather than using quantum computing alone to limit computation time, SurveyMonkey can pair it with edge computing. This will bring data storage closer to the device it will be influencing, which will reduce bandwidth and delay when the data is subsequently analyzed.

5) Haptic Technology

What if a client wanted to get feedback about a prototype, or wanted input relating to touch, feel or texture? Using haptic technology, SurveyMonkey could simulate the feel of the items in question hence augmenting user experience. The increased level of accuracy in the user’s subsequent decisions will help SurveyMonkey’s clients to obtain more precise data.

Each of these technologies in combination could efficiently provide SurveyMonkey clients with more accurate and relevant data — hence increasing client satisfaction. They could also augment user experience when completing surveys, which will in turn attract more prospective customers, enabling SurveyMonkey to further grow and innovate as a company.

Activator at The Knowledge Society | A Sandwich or Two Founder

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