Most businesses these days are collecting and generating data. While not all of them are investing in big data analytics solutions, most would agree that there is some value buried in the vast volumes of information that exist within modern IT ecosystems. As Business 2 Community contributor and marketing expert Heidi Anspaugh recently noted, this has several implications for customer intelligence, particularly within the B2B arena.
The three Vs
Even before the dawn of big data, the three Vs - volume, variety and velocity - often have applied to most analytics exercises. This has made business and customer intelligence more complicated to orchestrate effectively. Anspaugh identified three major shifts that are likely to overtake customer intelligence in the near future.
- Big data will become more essential
- Analytics tools are improving
- Customer intelligence will be disrupted
The first and final points are especially important to understand because they relate to some of the most prominent challenges that will emerge as companies attempt to better understand their customers. Because big data requires the convergence of information from many different sources, effective customer intelligence is likely to become more heavily dependent on sufficient B2B integration capabilities. So, even if the analytics tools themselves are improving, organizations that fail to adequately connect customer, internal and partner data would miss out on valuable insight. Another issue is that current methodologies may be ill equipped to handle big data even when just considering it from a volume perspective.
"The problem with many CI solutions - especially in the B2B world - is that they are simply incapable of keeping up with the sheer volume of data being produced and consumed by consumers," Anspaugh wrote. "This has forced a wide range of marketing professionals and CRM providers to re-think and reinvent how that data can be collected and analyzed."
From big data to better insight
As Anspaugh suggested, organizations will likely need to disrupt many of their existing processes and philosophies to prepare for big data. One core factor to keep in mind in pursuing these initiatives is that they should always be guided by clear objectives - the act of collecting data does not provide any value on its own. In fact, collecting and centralizing information can result in additional risk if the appropriate safeguards are not put in place.
This means it is essential to use the information to solve specific business problems. The potential value of big data is that it allows companies to draw on massive volumes of information to identify trends and then relate those findings to their own operations. For instance, language analysis has been used in a wide range of scenarios, including analyzing social media to track the spread of the flu. The possible uses of analytics may be endless, but companies cannot afford to spend time delving into an infinite volume of information, so it is important to narrow focus and to approach big data with specific business problems to solve.
For example, enterprises can could use language analysis to explore how their target audiences talk about certain products. This would reveal which product or service qualities are most important and lead to better business decisions. Knowing whether organizations in a particular region are more likely to respond to messaging with a focus on affordability or quality could be the key to successfully expanding marketing campaigns into new areas.
Regardless of how customer intelligence and analytics solutions evolve, the stakes of privacy and security are especially high in the B2B arena. Any big data initiative should be supplemented with a comprehensive plan for protecting sensitive information whether it comes from customers or business partners. Practices such as de-identification are helpful for reducing the risk to privacy, and any data that is shared for analytics purposes should only be sent through secure channels to prevent unauthorized access.
To learn more about how to move big data, register to view our webinar below.