Business analytics plays a pivotal role when it comes to customer engagement, acquisition, growth and overall retention. However, there are different forms of analytics that work in cohesion towards facilitating business growth. One of the most potent set of analytics cumulate into Predictive Customer Intelligence— an entrepreneurial tool that is currently being used by enterprises, quite extensively. If the basics are to be analyzed, Predictive Intelligence actually improves the bottom line of a sales funnel while reaching out to multiple customers— on a one-to-one basis. There have been instances where prudent inclusion of Predictive Analytics resulted in amplified ROI and helped organizations with additional sales.
Demystifying Predictive Intelligence
The underlining concept of business growth still remains the same i.e. personalized customer experience results in improved ROI. This concept is efficiently used by Predictive Customer Intelligence which offers a unique approach towards handling individuals while being mindful of their preferences. Moreover, the existing customer data is ingested alongside external tidbits, thereby minimizing manual analysis. To be exact, Predictive Customer Intelligence helps an enterprise create customer profiles— based on specific requirements. In the meanwhile, this profile can be used for gauging the overall behavior, buying patterns and even the scopes of engagement.
How PCI is Influencing B2B Growth?
There were times when marketers had to manually score leads by keeping a track of the existing sales funnel. Based on the analysis, marketers used to rate the leads— depending upon retention, loyalty and a host of other metrics. However, PCI quickens up the process by offering additional insights to the marketers. While the buying behavior of the prospect is taken into account, it becomes exceedingly easy to track the leads and determine the chances of conversions. The simplified approach is better termed as predictive lead scoring which makes use of Big Data for determining sales figures, opportune moments and even lead segregation while catering to the customers on an individual level.
When it comes to amplifying business growth via predictive analytics, businesses prefer searching public databases and social networks for convertible leads. The next step involves combining the procured information with internal data, specifically for finding optimal prospects. The best case scenario usually results in improved predictability of the existing conversions— at least by 38 percent.
Pairing Artificial Intelligence with Predictive Intelligence
There are companies which are already boosting up their Predictive Customer Intelligence framework with Artificial Intelligence at the helm. Although PCI is self-sufficient, it gets bolstered with AI innovations added into the scheme of things. With the likes of installed technologies and hiring trends added into the mix, the automated process of customer profile creation readily gets a boost.
The perfect concoction of PCI trends and machine learning basics help marketers gain better insights. With the evolution of Big Data, it often gets tedious for organizations to keep a track of leads and unstructured data sets. However, machine learning simplifies things further by adjusting programs with flexibility; therefore empowering bots for assessing customer requirements and responding to the same.
Apart from machine learning, Artificial Intelligence is also a potent tool for customer personalization. More often than not, enterprises find it hard to gather substantial data sets synonymous to the customer profiles. AI offers a completely new perspective when it comes to gaining insights by tapping into online stores, social media posts and even elusive databases. This approach makes customer profiling easier and assists the existing PCI module in the best possible manner.
In addition to all that, AI is a highly functional tool for growing a business when used in coherence with Predictive Analytics. The former can be leveraged for tailoring emails for specific customers just by looking at their profiles and purchase history. Based on a survey conducted by Demandbase, at least 80 percent of marketers are optimistic regarding the utilitarian nature of Artificial Intelligence.
Predictive Customer Intelligence: Trends and Future Scopes
According to the Aberdeen Group, predictive analytics is expected to increase the profit margin for enterprises by at least 5 percent. However, business growth is only possible if we start taking PCI seriously and follow the trends which are flooding the marketing arena.
Over the next few years, chatbots will grow beyond imagination. With bots in place, customers can readily get their queries answered without having to worry about time-based constraints. In addition to that, Garner predicts minimal human-to-human interactions by 2020 and expects chatbots to take over the marketing scenario.
Moving further, we are looking at a barrage of intelligent applications to work with. As predicted by TechCrunch, a minimum of 90 percent startups will soon be harnessing the power of machine learning for improving the existing apps. Following this development, we will also witness a rise in the number of marketplaces— dedicated towards intelligent apps.
Last but not the least, the growth of Big Data is improving the way enterprises look at predictive analytics. With PCI depending on machine learning and artificial intelligence, there has to be an information source for feeding insights into the databases. Without Big Data reserves at the helm, industries can readily fall apart even while implementing the PCI technologies.
Now when it has already been established that Predictive Customer Intelligence is the stepping stone towards futuristic business growth, the onus lies on the CISOs and IT heads for implementing the same with effectiveness. Marketers are willing to expand their domain and therefore PCI trends are now being skillfully paired with AI technologies and Machine Learning innovations.