Whether you’re running an international corporation or a small start-up, choosing the right data to drive your business is crucial to connecting with your customers. Part of this decision may be made for you by the very nature of your company – big data is a competitive and costly commodity, involving big investment. Apart from financial cost, other drawbacks often associated with big data include its impersonal nature – in effect reducing people to predictable machines, not to mention the suggestion that it is invasive. Nonetheless, thanks to the competitiveness of today’s markets, big data’s popularity is ever increasing.
Big Data – Big Opportunities
Big data offers companies opportunities that small data simply cannot, such as the creation of unique emails targeted to sections of a customer base and auto-generation of shopping lists. The strengths of small data, however, lie in the weaknesses of big data. Small data offers a detailed insight into the thoughts and emotions of customers. Via social media monitoring and interaction, companies can begin conversations with their customers and can tackle any potential problems quickly and effectively. In this sense, big data can be thought of as a back-office procedure, providing a large overview of trends in order to automate processes and generate profit.
Small data on the other hand, particularly in the realm of social media, can be a vital tool for building loyalty, trust and respect with your customer base. The real question any company should seek to answer then is not whether to use big or small data, but how they go about achieving the ultimate balance between the two. Rather than assuming that big is always better, the size and automation potential of big data should be combined with the human touch of small data, leading to both customer satisfaction and a profitable business.
Here’s an example of how a bank could use small and big data to retain customers:
Aoife visits her bank in Dublin at 11 am to withdraw money from her account, but her debit card is not working. Aoife is angry at the bank that their system failed to process her transaction. Aoife decides to get in line to speak with someone about her card issues, however there is a long line in the bank and she gives up after 10 minutes. Aoife writes their twitter account as she’s leaving the bank at 11:15 to complain about the failed transaction.
The bank doesn’t know that Aoife complained on twitter about her service because they don’t monitor online conversations. They may just have lost a long-term customer because they didn’t address the customers’ complaints. How can the bank solve this issue?
Bluenote Fusion Suite tracks mentions of the bank across Facebook, Twitter, Google+, LinkedIn, and the web. They see real-time data on whether mentions are positive or negative. So when Aoife tweets about her unfortunate experience, Bluenote Fusion suite catches the negative mention, reads it, prioritises it based on influence/importance, and distributes the message to customer service, or an automated queue for response. Aoife is sent a personal message apologising and promising that the bank will look into the issue.
Bluenote Fusion Suite notices more complaints than usual. By reviewing their timing and location, the platform discovers that people are tweeting and posting complaints about the same branch with similar issues. Bluenote picks up the trend and alerts the appropriate department promptly so they can address the issue on a larger scale These customers are prioritised based on importance and responded to in a timely manner.
Big data is all about picking up huge patterns and insights that can’t be gleaned from everyday conversation and interaction with customers. The end goal is an automated solution that increases monetization.
Small data, particularly in social media, is for picking up on immediate, actionable insights. It’s about finding ways to build loyalty, appreciation and brand trust. Spontaneity is one of its strengths. It catches social cues so marketers can respond like humans and personify their brand.
Using Bluenote Fusion Suite, the bank can track the frequency of customers like Aoife using various bank services, so they can target her with new promotions, and existing products, aimed at increasing the customers’ lifetime value. Based on the segment that Aoife fits into, Bluenote Fusion Suite automatically sends Aoife a suitable offer that will retain her as a client, and potentially encourage her to purchase more products through AIB.