We talk a lot in business about data being king. Integral to everything from performance tracking to strategy creation to customer experience, it even outranks money on the success hierarchy; after all, organizations can make the right strategic decisions if they’ve got the perfect information to drive them, and the right decisions typically lead to optimal operational efficiency and revenue generation.
Today the shape, speed, and size of data are shifting rapidly — the ways in which we create and consume it changing at unprecedented rates. Ninety percent of the world’s data was generated in the last two years; 2.5 quintillion bytes of data are created every day, and Google processes more than 40,000 searches per second. Five billion Snapchat photos and videos are exchanged daily, and an estimated 6 billion texts are sent every day in the United States alone.
Data’s becoming more visual, more conversational in nature, and increasingly interconnected, and it’s happening at a scale that’s difficult to tangibly comprehend — and with this explosive growth comes considerable complexity and pain points, particularly for the insights industry.
Conversation has always been at the heart of effective insights generation. In addition to offering context for a given situation, it provides human emotion and sentiment around topics — driving richer understanding of audiences and trends.
Take NPS scores, for instance. A quantifiable and well-loved business metric, the true value here lies not in the numbers themselves but in the why behind the scores. Why did customers give you that score? And what factors influenced their decision? That’s the real insight gold.
But opinion and conversation are difficult things to analyze at scale, given the manual coding and resources required and particularly in the volumes we’re dealing with today. Ultimately, it’s impossible to cost-effectively and efficiently generate insights from this kind of unstructured text data on your own.
This is why AI has revolutionized the world of insights generation. Used correctly, it saves countless hours of manual work, reinvigorates qualitative questions and methodologies, and opens up new sources of data for insight. Time and resource are also no longer prohibitive factors standing between you and rich insights.
Insights professionals are embracing AI technology at pace; according to a February 2022 Yabble survey of 200 professionals in the United States and Australia, 21% of specialists already use AI tools, and 53% say they expect to use them more in the future.
So it’s clear that AI is the way forward for researchers and insights experts — but how do you practically incorporate it into your insights program? Four actionable tips, below.
What kind of data do you have? Is it qualitative, quantitative, or both? Does it come predominantly from product reviews, social media comments, call center transcripts, live chat conversations, emails, survey responses, or elsewhere?
How much historical data do you have, and how much new data are you generating on an ongoing basis?
Where do data analysis and insights generation slot into your wider business strategy, and how often do you need to perform this analysis and generation in order to support company goals and objectives?
Answering these questions will give you a solid understanding of your particular insights needs and potential data gaps. You should also consider the specific benefits you’d like to see from an AI-powered insights tool.
Are you interested in saving time? Improving efficiency and productivity? Minimizing or eliminating manual work?
You’ll also need to figure out which types of insights will be most valuable for your business.
Is it getting themes and sub-themes from your datasets? Understanding the overall sentiment about a particular topic?
Perhaps it’s being able to look at your data over certain time periods in order to analyze and predict trends, or generating a detailed summary of insights with the click of a button.
Combined with your specific data and insights needs and the benefits you’re most interested in, this information should determine the AI-powered tool you choose to incorporate into your operations.
The right tool should make it quick, easy, and cost-effective to perform research and generate insights. It should be something that fits into your budget and that you can use on a regular basis to validate business strategy and therefore drive growth.
The right tool will enable you to incorporate insights into more aspects of your business — meaning you can structure your strategy based off what your data’s actually telling you instead of guessing at where your time and money are best spent.
A good way to ensure you’re properly leveraging your chosen platform for growth and innovation is to ask the right questions of your data.
Let’s look at Hey Yabble Query, the summarization feature of Yabble’s AI-powered insights generator. Query allows you to ask any open-ended question of your unstructured text data — “What improvements would my customers like me to make to the online shopping experience?” for instance — and then uses unique technology (a combination of custom-built Yabble prompts and the world-leading GPT-3 neural network) to generate a rich summary of answers to your specific question.
This type of AI-powered insights generation results in a remarkable depth and accuracy of analysis that can save you countless hours of manual work and give you a better-than-ever understanding of your audience and their needs, desires, and habits.
It also enables you to have a two-way dialogue with your data, hone and refine a highly targeted approach to research, and increase your ROI on insights generation.
Your insights program should generate knowledge you can use to directly guide and support business strategy. In other words: smarter, faster business decisions should be a primary benefit of the AI-powered tool you’re using.
Once you have your insights, then, the next step is to explore the details and to pivot your business strategy accordingly.
CarbonClick, for example, used the Yabble platform to gather information to help them ideally position their offering within the market and ensure they were meeting buyers’ needs. After undertaking their research project, they actioned the insights to exponentially grow their brand awareness and to drive early revenue.
Their exceptional results included a 100% booked meeting success rate, a 600% increase in LinkedIn followers, and a 270% increase in website visits.
You should also use your insights to refine your research program itself. Now that AI has removed the time, money, and resource barriers, you can implement regular and ongoing tracking, building a robust research methodology to support business growth and strategy. Perform monthly longitudinal surveys and drill-downs, undertake ad-hoc dips to help validate internal hypotheses, generate in-depth quarterly or yearly reports aggregating all your data sources — it’s about crafting a multi-pronged approach to insights that’s ultimately greater than the sum of its parts.
By using your insights to make business decisions, you can ensure you’re following a strategy validated by hard data. If the data starts to tell you something different (which you’ll know as long as you’re regularly performing insights generation as above), you can make the necessary shifts in a timely manner — consistently driving toward business growth and innovation.
Book a personalized demo to learn how the Yabble platform can revolutionize your business.