Why do you need Big Data to get Actionable Customer Insights?

Over the last few years, I had an opportunity to work with various sales, marketing, and customer service teams of various companies, small and large in size. Many of these executives have a notion that they actually have a “360-degree view of the customer”.

This means, “If you know everything, you must be misinformed.” Yes, some sales marketing professionals may need to be more informed about customer insights.

Data explosion during the last few years has impacted no other walk of corporate management than it has impacted customer insights. Ultimately, a customer is a living entity with an existence outside your company, and what your customers do in their lives matters a lot for your customer intelligence and, in the end, the growth of your business.

Big Data can be an important aid to sail through a sea of data. Without getting into the jargon, by Big Data, I am referring to tools and technologies to manage vast amounts of structured and unstructured data.

So, how do you know if your business can employ Big Data Technologies to get meaningful customer insights?

Your marketing Data Warehouse cannot provide all the data you need

You do have a ‘Marketing Data Warehouse,’ but parts of the organization do not feed data into the data warehouse. You recently acquired a company that has a wealth of data.

However, the two data warehouses do not talk to each other. Getting that one extra source integrated into the data warehouse may take much more time than you have to beat the competition. This may indicate the need for a ‘customer analytics sandbox,’ preferably using big data technologies.

Lots of data exists about your customers outside your data systems

External data is becoming more and more critical in customer insights. About a year ago, we delivered a data warehouse for a hotel management company where about 80% of the data was coming from external, syndicated data systems. Syndicated data is becoming more and more important in B2B marketing (for example, Dun and Bradstreet), hotel management (STAR, Demand360), and CPG (Nielsen, etc.). Many of these data sources are aggregated and anonymous but need to be correlated and compared with internal data.

Your customers are abuzz on Social networks

Social networks may be very relevant to your business for many reasons. It can be used to analyze customer networks, spending habits, specific technologies’ pain areas, the next possible buying need, etc. Almost every customer I have worked with in the last few years has started leveraging social media data to understand their customers. The question is not whether you need social media data or not but how you can leverage social media data for customer insights.

Data generated by customers is fast and real-time

Data generated by devices and sensors can provide important insights. One of our telecom customers augmented CRM data with customer behavior data captured through constantly streaming handset device data. This required a large ‘Big Data cluster’ to manage this constantly streaming and essentially vast amount of data. Our Gazelle is specifically developed to handle streaming data. Many companies track and capture the web interactions of their customers. Managing this constantly generated and complex data may sometimes require using Big Data technologies.

New’ Data startups’ are disrupting business in your field

Many traditional businesses are being challenged by new ‘data startups.’ For example, traditional lending companies and banks are experiencing competition from Fintech companies, most of which rely heavily on big data technologies for faster lending decisions. The same is true with Insurance companies. Are you into a business where traditional companies are challenged by ‘data startups’?

Your internal data may be difficult to manage and analyze

You have loads of data in customer service systems, sales notes, and interviews. But you need help to derive intelligence from this data. You have customer data in many different systems, but deduping customer data is difficult and may require expensive tools. These are some problems that have become more manageable with the advent of Big Data technologies.

You need faster insights

Your marketing and customer service teams may need insights about customers in real-time. They need to know the next best action for sales discussions and the best customer service rep to answer a question. To make this information available faster, you need supporting Big Data infrastructure that can collect, store, and churn data faster than you have been doing.

You need correlations, predictions, and segmentation with all this data

You may have all data cleaned and integrated into a single place. You are also capturing external and social media data. But this points to a need for complex mathematical models to churn vast amounts of data, predict the next best action, segment customers, predict buying propensity, cross-sell campaigns, etc. This needs huge computing power that can be made available easily by using Big Data technologies.

So, do you have any of these needs? The good news is that with the usage of Big Data technologies, customer insight is becoming enriched and actionable, fulfilling the promise of a real 360-degree view of the customer. We will discuss a few interesting examples of this in the next few articles.