Data analytics in marketing came of age with credit card companies in the United States, which used to send billions of direct mail pieces every year. While most of that went into the trash bin, the effectiveness of direct marketing proved far better than the mass media channels used previously.
“Those card companies and banks that knew how to leverage data had a substantial competitive advantage,” writes Raja Rajamannar, chief marketing officer of Mastercard and author of the bestselling book, Quantum Marketing. “Data was becoming the new currency to differentiate oneself and excel in the marketplace.”
As new technologies became available to leverage data and insights, there was the potential to create relationship-based strategies, as opposed to product-based strategies.
According to Rohit Chauhan, executive vice president of artificial intelligence at Mastercard, “There are three buckets of data: descriptive (what has already happened), predictive (what will happen in the future), and prescriptive (what the dimensions of consumer data are).” His analogy for prescriptive data is like having a GPS of insight, helping to find the best route to success. The success becomes greater with more refined data sources and new ways to analyze the data.
Banking Transformed Podcast Interview with Raja Rajamannar: Mastering Quantum Marketing in Banking
Sources of Infinite Data
The exponential growth of digital technologies, social media, e-commerce platforms and Internet of Things (IoT) devices has contributed to the exponential growth of data. Each interaction, transaction and engagement contributes still more information. The increasing prevalence of smartphones and the widespread adoption of internet connectivity have further accelerated data generation. Total global data volume is projected to reach 181 zettabytes (ZB) by 2025, according to Statista. That’s almost triple the amount of data created, consumed and stored in 2020.
Infinite data, which can drive enhanced personalization and customer engagement, originates from various sources across the digital landscape.
Social Media Platforms: Despite consumer concerns about privacy, social media platforms like Facebook, Twitter, Instagram, LinkedIn and YouTube generate a vast amount of highly valuable insights into users’ preferences, interests, behaviors and social connections. Marketers can leverage this data to create personalized marketing campaigns, target specific audience segments, and deliver relevant content to individuals based on their social media activity. These platforms also provide increasingly valuable customer service engagement options.
E-commerce transactions: Every digital engagement and transactionscreates a source of valuable insights. This data includes purchase history, browsing behavior, product and service reviews and customer demographics. Financial marketers are increasingly harnessing this information to understand customer needs, preferred channels and interests. By analyzing this data, personalized product recommendations can be generated, tailored marketing strategies can be tested, and targeted communications can be delivered. This enhances engagement across the entire customer journey.
Internet of Things (IoT) Devices: Connected devices are everywhere – from our smartwatches and fitness trackers, to our appliances, smart speakers and cars – collecting real-time data about consumer activities, behaviors and environments. This is exciting because financial marketers can deliver extraordinary experiences to consumers that are hyper-personalized, hyper-relevant and hyper-contextual. Every connected device has the potential to be a channel for marketing.
Continuous Connectivity:
If connected devices are advanced enough to tell doctors when their patients need attention, what does that mean for marketers interested in personalization and targeting?
Web Analytics: Web analytics tools provide useful insights into the origin of website traffic, how website users navigate and interact throughout a website, what content and web pages they’re most engaged with, and how they exit the site. Financial marketers can use this data to optimize the performance of marketing campaigns and the performance of various website elements. Marketers can also leverage web analytics to identify popular content, which can help with new product innovation and targeted communications.
All of these data sources have made the job of financial marketers much more complex, requiring that they radically reorganize their data infrastructure and capabilities. The sources continue to expand as do the technologies that can be used to leverage data. Most legacy systems weren’t designed to handle this level of volume and complexity — or the privacy and security needed to protect infinite data.
Read More:
- Mastercard CMO: Why Traditional Bank Marketing Is Failing
- Four Key Factors Impacting Bank Marketing Strategy
Challenges of Infinite Data
Timely execution: Infinite data sets require marketers to build models and test them at a speed comparable to the arrival of new data, balancing this real-time availability of data with the accuracy of models. Also, multiple models may work on alternative data representations at the same time, requiring many models to be evaluated in parallel.
Data intergration and analysis: The exponential growth of data can overwhelm most marketers, making it challenging to manage, process and extract meaningful insights from the vast pool of information. The complexity of integrating and analyzing data from various sources, such as social media, e-commerce platforms, IoT devices, and web analytics, requires advanced technologies and data analytics expertise.
Data validation: In addition, the abundance of data does not guarantee its quality or accuracy. Financial institutions must invest in data cleansing, validation and verification processes to ensure the reliability of insights derived from the data. Unfortunately, there is a shortage of talent with expertise in data analytics, machine learning and marketing technologies. The good news is that closing the skills gap is made easier since there are many third-party solution providers that can help with the organization and verification of data from multiple sources. This allows smaller organizations to improve marketing capabilities at a scale and speed previously impossible to achieve.
Internal data fragmentation: Integrating data from various sources provides the opportunity for a total experience (TX) that includes an enhanced customer experience (CX), improved employee experience (EX), a seamless user experience (UX) and a multichannel experience (MX) that will drive a stronger ROI. This can be challenging due to the fragmentation of data across different platforms and systems. Marketers need to have a robust data infrastructure that allows for seamless data integration, ensuring a comprehensive view of customer behavior and preferences. Siloed data hinders accurate analysis and prevents a holistic understanding of customers.
Data privacy and security: Finally, with power comes responsibility. As the volume of customer data increases, so does the importance of data privacy and security. Not only do marketers need to adhere to privacy regulations, such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), but there is a need to continuously review security measures around data and insights. These processes are critical to maintaining customer trust and avoiding legal and reputational risks.
Read More:
- Failing to Experiment with AI Tools Like ChatGPT Is a Mistake
- Five Megatrends Impacting Banking Forever
The Opportunities for Infinite Data in Banking
While the vast growth of data sources offers valuable opportunities for advanced financial marketing, it also presents challenges. Financial marketers must navigate data overload, ensure data quality and privacy, integrate fragmented data, respond to talent gaps, create highly personalized contextual communication and keep pace with evolving technologies.
Generative AI technology such as ChatGPT will soon be used to provide personalized customer support and engagement. It has the potential to handle customer inquiries, provide real-time assistance, and offer relevant product recommendations based on individual preferences and past interactions. This level of personalized engagement will enhance customer satisfaction, increase conversions and build brand loyalty.
ChatGPT has the potential to revolutionize customer interactions, enable personalized engagement, automate tasks, gather insights, and optimize marketing strategies in financial services faster than any of us can imagine. “This is only the tip of the iceberg,” according to Raja Rajamannar. More changes are coming, and the opportunities for creative marketers will be limitless.”