As technological innovation continues to evolve at a breakneck speed, new disruptive changes can emerge swiftly and unexpectedly. These technological advancements both contribute to and have shaped the ongoing data revolution, enabling companies to interact with customers and competitors in real time.
The field of market intelligence has been a clear witness to this synergy. Market intelligence operates by mining relevant data, and then analyzing and curating it to deliver particular insights. These include industry profiles, sales forecasts, customer trends, competitor developments, and the potential for expansion.
The development of intelligent tools, such as artificial intelligence (AI) and crowdsourcing, to efficiently analyze unprecedented amounts of data is thus poised to revolutionize the way market intelligence functions. Failure to sustainably incorporate such strategies can result in companies being overtaken by forward-looking competitors.
Artificial Intelligence and Big Data
AI has long been imagined and speculated about by scientists, researchers, and novelists alike, though its reality is now more present than ever before. In March of this year, Google’s AlphaGo AI made international headlines for defeating grandmaster Lee Sedol in the Asian chess-like game Go. Other applications have outperformed humans in identifying objects and languages, and many predict that car accidents will drastically decrease once self-driving automobiles become mainstream. These examples show that AI stands to not simply replicate human behavior, but to exceed human capability. AI holds competitive advantages in its ability to compute massive amounts of information.
These features are increasingly important due to the sheer amount of information available. The business consultancy firm Gartner predicts that, by 2020, there will be approximately 33 billion objects linked to the internet and transmitting data – up from an estimated 4.9 billion in 2015. These devices generate immense amounts of data. According to EMC, a data storage and computing company, there were 4.4 zettabytes of data in the digital universe in 2013. EMC expects this number to balloon to 44 zettabytes by 2020.
Further, the rise of the Internet of Things could revolutionize data collection by providing precise, targeted, and actionable information in place of unstructured text, voice, and video. For example, a smart fridge could detect when a user consumes a product, how much is consumed, and how often a product is repurchased.
The proliferation of Big Data – both in the quantity and quality of information – provides market intelligence with unprecedented resources, but also remarkable challenges in transforming those resources into actionable and meaningful insights. Even when equipped with statistical and data analysis software, the outright amount of information available is more than human analysts can process.
As processing power increases immensely year on year, the ability of AI devices to compute terrific amounts of data at brisk speeds is continually improving. Beyond sifting and aggregating information, AI can identify patterns from incomplete or noisy data and potentially emulate intelligent behavior to produce meaningful conclusions. In the future, AI will likely understand what type of information is useful for market intelligence and provide firms with precise and targeted information about the behavior and needs of various demographics of consumers, among other functions. Eventually, AI is expected to be able to act upon such analysis independently, continually honing its ability to understand context and develop more accurate high-probability behavior.
Crowdsourcing Market Intelligence
Data mining and analysis are not only being done by AI, but through crowdsourcing as well. Crowdsourcing is the practice of soliciting content, services, ideas, and feedback from diverse groups both offline and, more frequently, online. In many ways, market intelligence is inherently intertwined with crowdsourced research. In several industries, surveys and focus groups have long been a staple to collect the opinions, likes, and dislikes of customers. However, information gathering and decision making has traditionally been relatively rigid and top-down, as the researchers define the terms, scope, and targets of a given interaction.
Crowdsourced market intelligence offers several potential benefits compared to traditional methods. It is cost-effective, fast, flexible, two-way, and takes place in real time. Firms may promptly capture the information they seek, and might even discover ideas and perspectives they did not originally consider. Websites such as Facebook, Twitter, and Reddit offer extensive communities to tap into. Other platforms like Quora and LinkedIn generally present more reliable and professional communities that can be used not just to crowdsource consumer sentiment, but to receive direct answers to specific market intelligence questions and problems.
Looking forward, tools are being developed to take advantage of the knowledge of the masses to gather feedback and even analysis with greater reliability than other social media platforms. Crowdtap offers financial incentives to incentivize high quality activity for consumer insight, while Iarpa rewards users with prestige points and clout for strong and accurate security intelligence analysis and predictions.
Most of these existing services promote business to consumer (B2C) interactions. Conversely, Owler is a company aiming to carve a niche in the market intelligence industry by developing crowdsourced business to business (B2B) insights. An app it is currently creating aims to develop crowdsourced market intelligence by polling businesses on their thoughts about competitors on topics such as revenue, market potential, and employee strength. If successful, Owler could provide businesses with a transparent understanding of where they rank and how they are seen amongst industry competitors.
Crowdsourcing may not be suited to every industry, however. This is particularly true when expert opinion is required. Its utility is based on the market of operation, as different countries and regions have varying degrees of internet and social media penetration. Companies often underestimate the costs and challenges of developing an impactful social media and crowdsourcing strategy, which can result in wasted resources and embarrassing gaffes. That said, due to its reach and speed, crowdsourced market intelligence is increasingly useful as a complementary tool to procure information and business solutions.
AI and Crowdsourcing Disrupting Traditional Market Intelligence
Innovation in AI and crowdsourcing is not entirely distinct and separate. In fact, the two concepts are deeply intertwined. The ability of AI to conduct rapid and nuanced sentiment analysis on crowdsourced comments is fast improving. By observing subtleties in tone, attitude, and linguistic nuances, AI can identify customer opinions and trends without even asking for specific feedback. Developers aspire to augment these abilities through “computer understanding”, which teaches AI human morality and the intricacies of social interactions. Progress in this area could allow AI to autonomously interact and collect data from customers, thus delivering instant and higher quality market intelligence.
Although practical AI and crowdsourcing tools appear to be fast approaching, Microsoft’s disastrous recent launch of its AI Twitter user “Tay” is a reminder of their current weaknesses and limitations. Attempting to learn how to speak like an American teenage girl through Twitter conversations, Tay was taken down after it quickly started spouting racist, sexist, and otherwise inflammatory comments. Microsoft based Tay’s AI algorithms on the assumption of receiving honest and high quality crowdsourced interactions. Obviously, this did not go as planned, and Microsoft experienced a PR hit while failing to advance its technology.
However, though this embarrassing episode serves as a warning that AI and crowdsourcing still have a ways to go before they can be totally useful and reliable, it does not take away from their enormous progress and potential. Evolution and innovation in AI and crowdsourcing could fundamentally transform market intelligence. As a data-driven field, the emergence of AI may disrupt established practices by offering fast, accurate, actionable, and cost-effective services. Such technology may be seen as a sustainable disruptor, as AI will likely complement and further empower human analysts rather than wholly replace them. Human-machine synergy should be developed to define the scope and goals of market intelligence while considering broader knowledge and perspectives to form integrated analyses with actionable strategies.
Although the current course of development has indicated rapid progress in certain areas and deficiencies in others, neglecting industry transformations in AI and crowdsourcing may leave companies outstripped by leading-edge competitors offering superior intelligence. Consequently, an integrated and forward-looking business strategy must be adopted for firms to capitalize on technological developments to improve upon their market intelligence and avoid being left behind.
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