Data is one of the most valuable assets you can have.
The most successful companies have one thing in common - they use AI-based algorithms to analyze large amounts of data to predict what people want.
Jumpspark helps companies act like Amazon and Alibaba by using algorithms to analyze publicly-available data or your own company’s data. Through this, we learn what consumers want without needing to rely solely on surveys or interviews.
Examples
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Want to uncover the upcoming trends impacting your category?
We analyze User-Generated Content (ie. data from eCommerce Ratings & Reviews, Blogs, Forums, and Social Media) to identify trends that matter to your business
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Need to understand how people perceive your brand and competitive brands?
We use a two-pronged approach:
1) First we analyze User-Generated Content (eCommerce Ratings & Reviews, Blogs, Forums, Social Media) to understand how people are talking about your brand
2) We then supplement this with micro-surveys (ie. very short surveys) that provide additional information about how people perceive your brand across specific brand attributes
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Interested in identifying which product ideas resonate most with consumers?
We use micro-surveys (ie. very short surveys) to gauge interest in new product ideas using open-ended questions. We then use an AI algorithm to analyze the content of the open-ended responses.
Since the algorithm has been trained to identify language that indicates genuine interest in each product, this approach is more successful (vs. regular surveys) at predicting which ideas will succeed in market.
The algorithm is also able to identify how each product performs across specific attributes (perceived efficacy, value for money, etc.)
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Interested in testing which ads are most likely to drive your business objective?
We have a few AI-based learning approaches that can help.
Brand Linkage Testing: We can evaluate how effectively a digital ad is associated with your brand by running it through an AI-based tool that measures brand linkage. We can do this without the need for human feedback.
Overall Copy Testing: Similarly to what we do with Idea Screening, we can test ads by running micro-surveys with consumers, exposing them to the ad and capturing their open-ended feedback. We then use an algorithm to analyze the content of the open-ended feedback to gauge how effective each ad is.