Leveraging Big Data Analysis for Marketing: Key Points for Translating It into Effective Strategies

Among those reading this article, there may be quite a few who are already implementing "big data analysis" within their own companies or who have experience with it.The practice of conducting big data analysis to refine marketing strategies and understand target behaviors and needs appears to have become fairly widespread. However, it's also true that we're seeing a clear divide between cases where big data analysis is succeeding and those where it isn't. Here, we'll explain the challenges surrounding big data analysis and the key points for leveraging it effectively in marketing strategies.

Many cases involve poor internal coordination, preventing effective data utilization

Even when companies actively engage in big data collection and analysis, they often fail to utilize it effectively. A common reason is that they are not properly collecting data from both internal and external sources.

Looking internally, because the concept of "big data" wasn't widely understood before, various departments collected data individually, but the methods and formats were inconsistent. Even when attempting to refine marketing by linking and integrating this data, difficulties arise. Reasons include the challenge of consolidating data optimized individually by each department onto a single platform, or resistance to linking data in the first place.

Furthermore, data that cannot be obtained internally must be sourced externally, which naturally incurs costs when conducting surveys. Additional challenges may arise, such as uncertainty about how much data needs to be collected and over what timeframe. In such cases, initiatives like "Let's create a user app to reliably capture and manage customer IDs" may emerge.Developing a new user app to centrally manage customer information can make communication with customers easier and enable the collection of data usable for marketing.

This leads to app development, but various challenges are also emerging with these "user apps." A common scenario is: "We developed the app, but it lacks compelling features for users, so they rarely download or use it." This necessitates promotional efforts to boost adoption, adding further costs and making it unclear what the initiative is truly achieving. Such unfortunate situations are arising.

Start by reevaluating what kind of marketing you want to achieve

To avoid such failures, it's crucial to rethink "what kind of marketing we actually want to achieve" and to organize "what data we currently possess and what data is missing."

These steps might seem obvious, but in reality, it's not uncommon for companies to fall into the trap of collecting data without a clear goal. They might think, "Let's just gather all the data we have internally," or assume that "big data" requires massive volumes of information. Consequently, they end up collecting data without a clear purpose, scrambling to gather even unnecessary information, and expending excessive effort.

Of course, there are cases where it can be effective to gather various data and proceed with analysis, even without a clear purpose, to explore where customer needs lie and make new discoveries. However, if you proceed with data analysis without setting the scope or purpose for its use, it's often questionable whether it can truly be effectively utilized for marketing.

It is essential to revisit your company's business goals and clarify what kind of marketing you want to achieve and what initiatives should be prioritized to get there. From there, identify what data you should currently possess and what data is missing. Going through this process to thoroughly consider what data is truly necessary for your company and how to collect it most efficiently and effectively is paramount.

First, deepening relationships with your current customers is vital

Re-examining your business goals may shift the perspective from which you evaluate your data collection and analysis methods. For instance, many companies today prioritize "acquiring new customers" to boost revenue and implement marketing strategies accordingly. However, recent years have seen a significant rise in the importance of "preventing churn among existing customers" and "maximizing LTV (Life Time Value: the total value a customer generates over their lifetime)."Of course, wanting to attract new customers you haven't met yet is important, but it's also a difficult challenge. In some cases, getting 100 existing customers to use your service more frequently and for a longer period may be less costly than acquiring 100 new customers.

Furthermore, while obtaining detailed user information might be difficult for businesses entirely offline, digital services can gather various data during transactions. This means you likely already possess a wealth of customer data that simply isn't being utilized. Therefore, leveraging your existing data and considering it from a perspective like "How can we prevent customer churn?" might yield new insights.It's easy to think that big data analysis requires gathering large amounts of new data not yet in your possession. However, why not first set the goal of "deepening relationships with customers you are already connected to" and consider what you can do with the data you already have?

On the other hand, we understand that many teams face the challenge of having marketing goals but lacking clarity on what data is needed to achieve them. That's where DENTSU CROSS BRAIN INC., with its team of experienced data scientists, comes in. We offer a service called "Primary Check." This service designs data utilization plans tailored to the state of a company's existing data and supports the practical implementation of data marketing.You could call it a service that "assesses the value of the data you currently possess." From a data scientist's perspective, taking stock of "what can be done with what you have now" can be highly effective. Why not start by reviewing your company's existing data?

It's not about "analyzing massive amounts of data = big data analysis"; what matters is the purpose and method of using the data. Are you fully analyzing the data you possess? What kind of marketing do you actually want to implement? By returning to these fundamental questions and reassessing your company's approach, you can prevent data collection from becoming an end in itself, which only increases the burden on stakeholders. Remember: no matter what tools or solutions exist, their implementation is not the goal. Instead, focus on how to leverage them to achieve your desired business objectives.