Marketers and executives are always wondering how to make their campaigns more productive and effective via multi-channel communication with the support of emerging self-learning and decision-making technologies is always something financial services are eager to implement. implemented. The article discusses these technologies and how to get the most out of them.
The continuous increase in the size of the financial services market calls for innovation!
Multi-channel campaigns have been a favorite recipe in digital marketing campaigns these days, according to The Business Research Company’s Global Market Report 2021, the financial services industry is growing by $22.5 trillion in 2021 and is expected to reach $28.5 trillion. Haven’t we repeatedly come across a digital ad or an email talking about how good a certain credit card or checking account is or how to invest money better? The financial services industry is one of the major users striving to use technology as much as possible to deliver the right message to retain, upsell, cross-sell existing customers, acquire new potential leads and nurture that relationship with communications in the B2B and B2C space. .
To achieve these goals while maintaining scalability, technologies such as artificial intelligence, data analytics, blockchain, and RCA could be leveraged for more than we could aim for.
Here are the top 4 rising technologies and the cross fusion of them used in digital marketing in financial markets.
1) Artificial intelligence
Although FinTech companies are using AI to process customer requests and transactions, for example, several retail banks have used chatbots to manage customer issues and day-to-day processes. There is no doubt that AI brings a lot of automation to this, but it can significantly improve communication channels by identifying precise segments and predictions backed by analyzed data on customer preferences, past interactions. AI-based segmentation can derive decisions on multiple factors, transactions, demographics, firmography, geography and more to predict the likelihood that a particular group of customers will decide to make the next financial decisions, trends and investment choices. In turn, AI also reduces information asymmetry and transaction uncertainty.
The application of “artificial intelligence” technology in the financial sector also plays an important role in content customizations, aiming at the right time for personalized services. An example: How many marketers or database analysts wonder when would be the best time to send an email marketing campaign? Instead, many emails are sent in bulk today. With machine learning, it is possible to determine the optimized time when someone opens their emails, ensuring a higher open rate and click-through rate. A Deloitte study shows that 56.5% of companies use AI in marketing for content personalization Predive analytics.
In customer segmentation, different aspects of AI such as machine learning, computer vision, natural language processing, self-supervised learning jointly accelerate the flow of real-time financial information and derive a tree a specific decision tool, a propensity model, or a support vector to achieve a specific goal. and derive personalization for customer groups.
Blockchain is already exposed to applications in digital currency, cross-border payment, securities clearing, trade finance, cross-chain protocols, hybrid collaborative innovation and DeFi (decentralized finance ) reducing the operating costs of financial institutions. Blockchain can play a vital role in –
- Target audience identification: With an automated set of rules, campaigns can accurately identify customers without risking taking advantage of inflated metrics. Engagement will not only help existing customers, but increase leads and subscribers.
- data management with the use of the right KPI simply for decision making for the next best treatment for customers.
- control and personalization – dynamic ads, banner placements and content personalization can be made much easier.
Due to the decentralized nature of blockchain, marketers can collect all campaign metrics without any misinterpretation, which would ultimately help paint an accurate picture.
3) Robotic Process Automation (RPA)
Financial institutions often use robotic process automation (RPA) to eliminate manual errors by speeding up compliance processes, increasing procedural efficiency, or account reconciliations, although there are use cases where RPA can be leveraged to optimize digital marketing processes, as executing marketing campaigns is a repetitive task. !
Improve customer engagement – With the rise of Robo Advisors and Self-Financial Planning. Improving the experience means a lot to drive the conversation from start to final conversion. Robotic processes can leverage autonomous, unattended bots to react to customer keyword inputs, a good example is the integration of chatbots enabling compelling discussion with customers and delivering repetitive search results to marketers.
Another feature of RPA is to maintain consistent data, expedite record-level assignments across multiple systems, which greatly contributes to much faster prospect engagement.
With the added benefit of using machine learning with robotic process automation, applies algorithms to learn information and leverage experienced decision making in addition to specified rules. This reduces the heavy time dependence on repeated analysis of online ad placement campaigns.
4) Cloud computing and big data
Organizations typically collect, store huge amounts of data and use it for targeted use cases, but data is often scattered across multiple business units and in different formats and poses challenges in unifying all consumer profiles . Cloud services provide database marketers with scalability, computing power, functionality to find big data insights in real time, and can enable decision making for marketing enablement, as an alternative to building all the infrastructure, data centers and designing solutions that cost a fortune. When it comes to leveraging cloud computing, let’s compare 3 types of services based on what’s on offer and when to use them:
- Infrastructure as a Service (IaaS): e.g. storage and servers from AWS, Azure, Rackspace, Linode, Google. Organizations get more control but need a team of professionals to manage applications, data, middleware and operating systems.
Who can use- Organizations looking to control comprehensive applications and infrastructure usage, budget concerns, or businesses that are growing rapidly and need scalability in the near future.
- Platform as a Service (PaaS): For example, where developers can build applications, automate in addition to services provided by AWS Elastic Beanstalk, Google Application Engine, or IBM Bluemix. Highly available and easier deployments, but complex integrations and data security issues on personal consumer data.
Who can use – Organizations looking to create their own martech analytics applications, flexibility on project deployment worked by different teams of developers.
- Software as a service (Saas): these services practically use it such as Hubspot, Adobe Creative Cloud or Salesforce. Sales reps and marketers directly install an app or use a web browser. Organizations don’t need technical development teams or spend on hardware or software maintenance, but have almost no control over applications, servers, and limited customizations.
Who can use – Businesses looking for a quick and easy way to launch their marketing engagement faster without wasting time on service, hardware and software maintenance.
Advancement in technology is the driving force that has facilitated the emergence and growth of digital marketing. Financial services with ingrained legacy processes have often struggled with technology migrations, but the pandemic has given executives and marketers a new perspective to leverage deeper insights by creating an omnichannel experience. As a global nature of financial products and services, technologies driving marketing are an essential part of the organization for lead retention and generation. As technology and automation continue to evolve, automating digital marketing campaigns will become easier and widely used.