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The Good(?) Old Days
Those of us who have used the Internet for decades may remember a time when searching for a website meant working your way through carefully curated content categories and using a boolean search to filter websites from those categories. The idea was similar to finding a business in the phone book, or using the Dewey Decimal system in a library. It was essentially taking the way we had always done things and making it digital.
In those days, Yahoo was king (although you could also ask an infamous butler named Jeeves, among others). Yahoo had a small army of people classifying websites into their predefined categories. It took an incredible amount of work to curate those categories, and it required that users think like Yahoo.
The results weren't very good, but it was definitely better than nothing.
Then Google Happened
Google took a radically different approach to the problem. The idea was to collect everything and then determine what was most relevant based on the pages themselves, and the relationships between pages and websites (see, for example, PageRank: http://infolab.stanford.edu/~backrub/google.html).
Suddenly, Google would give you exactly what you looking for and all you had to do was ask in normal, everyday language. You didn't need to know how Google stored or organized their data. And, most importantly, you could you could find things you didn't even know existed. It was just about magic.
Google very clearly won the search war. And the key was that it no longer relied on people processing the data. Rather, Google used the power of graphs and clever ways to exploit them in order to determine relevancy.
Search Then vs. Marketing Technology Now
Fast forward twenty years and, somehow, we still have a similar battle in marketing automation and marketing technology platforms.
Most existing marketing automation and CRM platforms rely on a rules-based approach similar to the old human classification approach that early search portals used. A lead may get +1 for reading a whitepaper, +5 for watching a video. Add them all up for the lead score. (Now, where those numbers and rules came from is usually quite a mystery...)
The rules-based approaches, although better than nothing, are not very good.
Moreover, such rules-based systems are time-intensive to create and maintain. They cannot handle a large number of variables or sequences of events very well. And, even if they were somehow perfectly created, they could be obsolete in just a few months when customer behavior changes.
The existing rules-based platforms are not serving salespeople or marketers very well. Such systems must yield to an approach that continuously learns and minimizes the human time required to do so. Such rules-based systems are ripe for disruption.
Click360's approach to existing Martech is what Google's approach was to Yahoo! and Ask Jeeves. Click360 applies Deep Learning (a type of artificial intelligence), and unsupervised learning, to understand each of your customers and help your sales and marketing teams best engage them.
Marketing teams no longer need to create time-intensive rules--they are learned directly from observing your company's customers, and they get better over time. They can prove their ROI directly, and they can focus on generating exactly the kinds of leads that convert for their sales teams.
Sales teams, on the other hand, get actionable insights in their existing CRM (meaning, they don't need to log into a new system). They can prioritize their time by contacting the leads that are actually the most likely to convert--not just the leads who have been the most active. Accordingly, they can improve their sales efficiency, and at the same time improve the marketing return on investment.
Being the keen observers of history that we are, we think Click360 is on to something and set to disrupt the existing Martech platforms. Come be a part of the future and see how a continuously-learning approach can help your sales and marketing teams best engage your customers and maximize results. Contact us today to get started.