Take your competitive analysis to the next level with AI
AI-driven competitive intelligence exposes opportunities and threats as they happen, with contextual insights that move you to act
In a previous article on competitive analysis, we addressed two key ideas:
- Your customers and competition are constantly evolving in a number of ways
- To keep up with these changes, the use of new and emergent technology is essential
Companies have begun adopting artificial intelligence into their processes in a variety of ways, for a variety of reasons. Take a look at the number one reason in this study by Statista, though:
The language is crystal clear: 84% of responding companies say they’ve begun using AI to gain or sustain a competitive advantage. So, if for no other reason, your company should at least be considering adopting AI in order to keep up with their competition. To do so, you need to fully understand just what these tools are truly capable of.
Augmented analytics is the next wave of disruption
The use of AI for competitive analysis goes much further than automating the process of collecting, organizing, and communicating information regarding your competition. To be sure, these simple processes are table stakes by today’s standards.
So, as we said earlier, it’s the companies that take full advantage of all that AI has to offer who will experience major sustained success. Case in point, Gartner predicts that, by 2020, competitive analytics tools that involve AI will deliver twice the business value of those that don’t.
The reasoning behind Gartner’s prediction is simple:
AI-driven competitive analysis tools augment the data being collected in a number of different ways, providing valuable insight to the user (i.e., your company) that they may not have been able to uncover on their own.
AI is disrupting the realm of competitive analytics by enabling companies to generate all this valuable insight with relative ease. Because these organizations can now rely on AI to take care of the “on-the-ground” initiatives (i.e., from data collection to data analysis and reporting), said teams are able to invest more time and energy into proactively improving their business and getting an edge. On the flip side, the company that doesn’t use AI-driven tools will, of course, not have the same excess resources needed to sustain the same amount of growth moving forward.
So, it’s clear that AI-driven tools are poised to disrupt the competitive analytics realm completely—and even clearer that companies that use these AI-driven tools will be able to completely disrupt their respective industry, as well.
Now, let’s dig into how this all plays out when put into action.
4 key ways AI augments your competitive analysis efforts
Without further ado, let’s take a look at the most impactful ways AI can take your competitive analysis initiatives and efforts to the next level—and allow you to becoming a dominating force in your industry in the process.
Keeps you on top of the data
In focusing on competitive analysis, one of your most basic goals is to be able to collect data and information on your competitors in near real-time. Any downtime between when a competitor takes a specific action and when you react to said action is time lost that will essentially hold your company back from the rest of your industry.)
With AI-driven competitive analysis tools, the information you’re receiving is as current as can possibly be. These AI-driven tools also automatically and instantly interpret this data as it comes in—much quicker and more efficiently than your team could possibly do “by hand.”
If we’re strictly talking about streamlining your competitive analysis processes altogether, investing in AI-driven technology is basically a no-brainer.
But, as we’ll focus on throughout the rest of this article, this is merely scratching the surface of what AI-driven competitive analysis can do for your company...
Provides context to the collected data
Most competitive analysis tools—whether they involve AI or not—allow teams to automate the process of collecting, organizing, and presenting data. But, for companies that use tools not driven by AI, the process of giving this data meaning by wrapping it in context is still up to them.
(And, to be sure, skipping this step is not an option. In order to make improvements that matter to your business, you absolutely need to know what this data “means” within the context of your industry. Otherwise, it’s just words and numbers on a screen.)
Unfortunately, this is a monumental—almost impossible—task for even the largest and most efficient marketing team. In fact, over 90% of marketers admit to deleting or otherwise disposing of data without taking the time to even read it, let alone fully understand what it means.
Companies that do utilize AI-driven competitive analysis technology, on the other hand, will be privy not only to the “on-paper” data in question, but also to any supplemental data that can provide deeper insight into the meaning behind the numbers on the page.
This can benefit your competitive analysis initiatives in two key ways:
- AI automatically puts your important data into context, allowing you to get a more holistic view of the data in question
- AI automatically determines what data is not necessary or important in a specific context, allowing your team to pare away at vanity metrics and the like
Identifies the sentiment behind data
If you’ve been keeping up with developments in AI over the past decade or so, you’ve likely seen how far the technology has come in terms of understanding the sentiment behind certain data.
AI tools today are able to discern the connotative meaning of a given piece of information—and use this understanding when reporting on the data. To be sure, without this ability to understand sentiment, your competitive analysis tool may end up pointing you in the wrong direction.
For example, let’s say your competitive analysis tool comes across this recent review of a competitors’ product:
Clearly, this review is laden with sarcasm, and shouldn’t be taken literally. Without sentiment analysis, though, the review might simply be grouped in with all the other four-star reviews—which will skew the ensuing reports one way or another.
With sentiment analysis, though, your competitive analysis tool will be able to pick up on the subtext of a given piece of information, and automatically make adjustments in its organizing and reporting of data as appropriate.
(For more on this topic, check out our post on Sentiment Analysis.)
Identifies affinity within data
Emergent AI technology is also able to identify the affinity behind certain pieces of data and information, as well.
Most often, this information and data involves your competitors’ customers and target audience. What emergent AI tech does, here, is to analyze and assess the context and sentiment of the consumer’s actions, behaviors, or language in order to better understand the relationship between said consumer and the company in question.
With this enhanced understanding of the consumer, these AI-driven tools can provide in-depth insight into what drives them to become loyal to certain brands—and suggestions as to how your brand can take advantage of this information in the future.
Throughout this post we’ve focused on the importance of using competitive analysis to:
- Keep track of trends and goings-on throughout your industry
- Identify opportunities for growth, as well as the underlying context behind these opportunities
- Act on incoming intelligence and data in a way that will make an impact on your industry
With a robust arsenal of AI-driven competitive analysis tools at your side, making this happen will be a cinch.