The Number 1 Rule of Big Data For Decision Makers
The use of Big Data and data analysis holds a great deal of potential for businesses. Businesses have forever been collecting information about the behaviour, demographics, purchase patterns, and buying preferences of customers.
But here is the clincher – less than 25% of businesses are not making the most of what is straight in front of them. Having huge amounts of data is not enough - you must be able to analyse and interpret it in such a way that it yields important insights you can use to improve your business.
Past behaviour often guides future behaviour. By analysing the behaviour or preferences of the customer, you can be more strategic in your communication, providing you the ability to build a deeper connection with your customers.
How do I use Big Data to Understand my Customers?
By properly analysing data, you have the potential to know what your customers want, even before they realise they want it.
Big Data has huge benefits for an organisation in its journey to better understand the individual customer and the market as a whole. Dig into it to find data points that paint a picture of how your customer interacts with and feels about the brand and products or services.
Here are some of our tips on using Data to understand your customers:
- Consolidate all the data and study it on one platform. This ensures you’re not missing anything and makes it easier to find buying patterns.
- Prioritising data quality over quantity is important, and focus on relevant information. Since we’re talking about what your customers want, data such as buying preferences and past purchases will be useful.
- Be as agile as possible in your promotions and campaigns. Customer motivations keep changing and are impacted by many external factors. Thus, you’d want to regularly gather and analyse data to ensure that you can adjust as necessary and develop the most relevant offers to your audience.
Look at your data holistically. Find all the touch points with your audience: website, social media, email, and other channels. Determine what platforms they use (e.g. desktop, mobile) as a complementary data set. Correlate and interpret the data, considering your customers’ actions and motivations.
Data Insights for the Customer Journey
The customer journey has become a critical part of marketing. In a nutshell, it’s the roadmap from an initial connection to conversion, purchase, and after-sales.
One of the key challenges for harnessing data is that the business users are not connected to their data. The common way for a business user to access data is via pre-defined dashboards or reports. This is great for operational efficiency, but this restricts the innovation potential. If an organisation is thinking about digital transformation, then they need to think fluid data connectivity – removing the restrictions of pre-defined reports; and connectivity because they need to connect business with the data without reliance on teams of data scientists.
You can use predictive marketing—defined as the analysis of existing customer data to identify patterns and predict future trends and outcomes—to make predictions on what your customers may want in the future in terms of products, services, or customer support.
Every touch point expands the story of your customer and reveals much more about what they like, which marketing and purchasing channels they prefer, and the purchasing methods they frequently use. This 360-degree view gives businesses a more in-depth view of customer behaviour.
Big Data offers a vehicle to harness all those customer insights and develops a comprehensive portrait of your ideal customer. How can you use this “portrait”? Data is nothing without context. Proper analysis delivers actionable insights that you can use to improve your customer personas. This, in turn, enables you to expand your ability to anticipate what your customer will want in their customer journey and experience, based on your improved customer personas.
Just looking at past data is not sufficient to make intelligent predictions about the future. Past data inherently includes bias. What is required is an intelligent way to add business knowledge to the mix too. We call this taking a deterministic (Knowledge) + Probabilistic (Data) approach. With this predictive analysis you can use predictive marketing to get a better idea of what a customer will want as well as inform you of what campaigns will work best. Once you turn people into customers, you can use Big Data to know how and where you should communicate with them. This is especially important since bad customer service can really cost you. In fact, according to recent studies, 68% of customers say they would switch vendors due to poor customer service.
Social media can get you a real “pulse” on what your fans or customers currently like. Look at data from relevant social media platforms and pay close attention to engagement metrics as well as conversion metrics. This can inform your social media marketing strategy. For example, if you know your social media followers respond well to a particular product, create a Facebook ad for that product and target users who have a similar profile to those who have bought it. You can go one step further; with this data, you’ll have a better idea of your customers’ preferences and use it to come up with more products that reflect the characteristics of the current and past products which became “big hits” with your customer base.
How do I get the best out of my Big Data plan
While knowing what your customers will want, even before they realise they want it, may seem like magic, Big Data can actually bring you a lot closer to this goal. However, as we always stress, data is only as good as how you use it and the insights that you get from it. You still need proper analysis and interpretation to make it effective.
For more information on Data Strategy and Solutions, or how Diversus can innovate and transform your business operations, contact Dien Tang (Director/Principal Consultant) on 1300 888 900 or firstname.lastname@example.org