Yet research says those transformation efforts fail most of the time. Why? Perhaps there are many reasons: strategic mistakes with goal setting, tactical flaws in planning, operational errors during execution. In this article, I shall narrow down these issues, those that are largely in our control, and suggest a few ways to overcome them.
1. Don’t let FOMO be the driver.
Put your horse before the cart. A competing bank’s marketing campaign focused on NFT-backed digital artifacts for loyalty exerts a lot of pressure on all peers. But before onboarding a vendor to provide the backbone for crypto assets, the marketing team should list a handful of concrete use cases and assess their relevance/appeal to the bank’s customer base.
For instance, create a concrete use case like this:
“My Telco X shall mint 1,000 celebrity-signed SIMs accompanied by a collectible, say a coffee mug or watch, and distribute it to our most loyal customers. The SIM and the collectible are digitally coupled and tokenized using NFTs, making this a limited-count asset now. Customers (may) take pride in owning it. We may incite demand as the asset is limited. We may host an exclusive “Celebrity Collectible Owners Club” with the access key being the NFT itself.”
And if it sounds logical, then onboard a partner to realize the vision.
2. Remove self-imposed constraints.
Most enterprises lock themselves in with only one vendor for a specific function and let them handle the entire customer base. For instance, one vendor for CCCM, one for RTIM, one for digital analytics, etc. And each one of them caters to the whole base of 100 million customers.
Enterprises seek advanced capabilities like A/B testing from those products but do not themselves practice A/B testing with multiple vendors, where, say, two competitor products are pitted against half the customer base.
In today’s contemporary tech landscape, with most vendors taking the SaaS route, operational considerations of yesteryears should not be held as blockers for having multiple incumbent competing products.
3. Diffuse the tension between IT and business.
A common trait I find in market leaders is the presence of absolute synergy between IT and business. Meanwhile, I notice the opposite in laggards. But both are wrong and need a realignment in order to put the end customers ahead of their own priorities.
Having IT and business aligned on the right “customer” axis is pivotal to ensuring smooth and successful outcomes.
4. Don’t go for blind AI; seek explanations.
It is sad but true that even large enterprises fall prey to machine learning’s (ML) glamour and onboard many AI-heavy projects, allowing their systems to make a lot of decisions without sufficiently understanding the rationale behind them.
In their race against time, enterprises have a tendency to choose those vendors that ship with a lot of pre-built models, and knowing the trend, vendors have also inflated their stock model count. This is a potentially dangerous practice, one that can uproot a brand’s stated emphasis on customer centricity. Enterprises need to make sure they choose vendors that can provide a rationale, in business terms, for the recommendations and actions they undertake, and not go by arbitrary numbers emitted by mathematical models based on never-understood matrix transformations.
For example, if Alice was recommended a four-year mortgage loan while the CSR opines that a three-year unsecured loan is a better option, the CSR should be able to ask the underlying ML as to why it deemed mortgage to be a better option for Alice. In response, the ML should be able to give reasons in business terms (e.g., “Analysis of Alice’s cohorts reveals that there is a 3x increase in chances of bad debt when they consider a loan within six months of engaging with the bank” and not an apparently useless metric (e.g., “Alice’s proximity score to four of the deduced clusters is 0.3, 0.4, 0.1 and 0.2 with a noise level is 0.86—that’s my recommendation”).
5. Be rational and also understand the data limitations.
I have sat through business workshops on customer centricity where the need for brands to connect with the “whys” behind customer engagement is well understood, and then, we come up with a purpose for customer interaction like “To open a fixed deposit for 12 months.” There is an apparent disconnect here.
An end customer like Bob will possibly engage with an intention of “Putting idle money to better use” and possibly wants a safe bet. Hence, his preference for deposit over equity. Thinking from Bob’s perspective, fixed deposit is just a means, not his objective, and until you understand this subtle difference and align accordingly, you will never be able to transform your company into a truly customer-centric brand.
While there is no prescription for success, as Otto von Bismarck rightly said, the wise man learns from the mistakes of others. Not rushing into the same pitfalls others have just managed to come out of is important to stay on the right track.
Want to know how Pelatro can help you improve your customer engagement? Get in touch at hello@pelatro.com
Author
Chief Architect at Pelatro. Proud to help 40+ Telcos/BFSIs offer the finest contextual marketing experience to their 1B+ subscribers. Read Pramod Konandur Prabhakar’s full executive profile here.
This article was originally published here.
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Gone are the days where customers were happy with only a waiver on late-payment fees. While everyone enjoys freebies, they don’t always translate to increased assets under management or loyal customers. That said, taking an iron-fist approach with profits to please the board can cause an enterprise to fall from grace with customers.
How BFSI Marketing Teams can find the Right Balance
Enterprises are aware of this friction. Businesses need profit, and the management is accountable for investors’ money. Customers, on the other hand, expect to be pampered. BFSI enterprises are having trouble finding the right balance. They generally take one of two approaches:
1. Top-Down: With this approach, the business goals and targets are set from above. Sales and marketing divisions are tasked to achieve these goals, and customer experience can take the back seat.
2. Bottom-Up: With this approach, CSAT scores and customer priorities take the front seat. Key result areas are generally tied to sales without accounting for costs. These companies are busy acquiring customers and keeping them happy while profitability takes a back seat.
That said, banks—like most companies—must find ways to balance these two approaches. Here are a few ways to find that balance:
1. Make both “customers interests” and “enterprise objectives” CMO/CSO priorities.
Enterprises should discover the whys behind customers engaging with their brand. They should nudge those customers toward their individual goals using the enterprise’s product offerings and experiences. In doing so, they can’t assume an infinite supply of resources or cash. The products and discounts—including any freebies and vouchers—should be rationed from a pre-allocated budget.
For example, when John visits a bank’s website and clicks a few times around the 8PC_Personal_Loan_1Y product, he shouldn’t be incessantly nudged toward signing up for that product. The bank must first establish a connection with John’s underlying purpose, which could be “short-term credit need.” After that, the bank should work out the case from John’s perspective, taking into consideration his assets and liabilities, products held, credit rating, etc. Finally, the bank can recommend multiple products that help him realize his purpose, which might include “loan at 2% on top of his deposits.”
When recommending the 2% deposit product to John, sales and marketing should be aware that they may be doing so at the expense of possibly recommending the same to Alice, as there should be a rationed quota of products to sell to achieve the desired profit margins.
2. Build hierarchical journey plans.
Based on the above example, banks must build three kinds of customer journey plans: strategic, tactical and operational.
A. Strategic journeys focus on objectives and verifiable targets but do not specifically talk about means to achieve those targets. They always work on aggregate milestones—not in an individual customer’s context—and may cover multiple objectives.
For example, the bank could lay out the quarterly revenue and sales targets with monthly milestones alongside broad annotations:
Month 1: $2 million investments, 25,000 new product sales
Month 2: $1 million investment
Month 3: $3 million investment, 50,000 product sales
Overall goal: Of the 75K new product sales, at least 50% should be upsell and 30% cross-sell.
B. Tactical journeys are defined in the context of individual customers. They don’t carry a complete prescription of all steps from start to end of the journey, and they can have multiple branches along the way. They are defined on a persona and may delegate orchestration to operational journeys, which are described below.
A good tactical journey caters to a single objective from a strategic journey. The bank could, for example, define the five-months journey for first-time-earner persona. This could include monthly guidance milestones to assess progress at the individual level as well as triggering campaigns at stipulated intervals or in response to certain user activity:
Month 1: Ensure no customer complaints and all KYC are complete.
Month 2: Complete zero-party data survey.
Month 3: Recommend two products based on behavioral and contextual data.
Month 4: Check if the customer has signed up for at least one new product since onboarding.
Month 5: Assign a persona based on portfolio value and take a first guess at CLTV.
3. Operational journeys are largely contextual in nature and do not necessarily align with any specific business objectives. They are reactive in order to provide the best customer experience.
A detailed flow diagram, for example, should be based on personalizing engagements by taking into consideration user clicks, activity and inactivity on the banks’s website and app. In doing so, stitch together user actions across channels—such as KYC completed, responded to surveys, etc.—in order to have holistic context for nudging customers.
4. Implement strategies and adopt technology to achieve business goals.
Once journeys are developed, banks should revitalize the marketing and sales activity to align with the hierarchical journeys above. During this process, the CMO and/or CSO team should define top-level strategies alongside enterprise goals and operational constraints.
Technology plays an important role here. For example, domain specialists and analysts punch in the broad outline of tactical journeys, while technology, such as an ML-backed enterprise marketing tool, can take responsibility for curating the actual operational journeys.
Conclusion
To realize large successful business transformations, BFSI enterprises need to maintain equal focus on CSAT and profits. They need to work out a sales and marketing strategy where enterprises serve as a bridge helping customers meet their personal financial goals without taking blind-folded customer-centricity approaches.
Sound journey planning leveraging on strategical, tactical and operational journeys while empowering teams with technology. Only then can companies find the right balance to serve both customers and investors.
Want to know how Pelatro can help you improve your customer engagement? Get in touch at hello@pelatro.com
Author
Chief Architect at Pelatro. Proud to help 40+ Telcos/BFSIs offer the finest contextual marketing experience to their 1B+ subscribers. Read Pramod Konandur Prabhakar’s full executive profile here.
This article was originally published here.
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Leads operate in a no-mans-land between two powerful departments inside banks—sales and marketing. A successful lead curation strategy requires dedicated efforts and collaboration between the sales and marketing personnel.
Are Leads a Sales Function or Marketing Responsibility?
Sadly, leads fall under one of the two in most banks, while it really demands more of an overlap. The marketing function is the think-tank while sales functions as the workhorse. The modern-day lead governance recipe needs data-driven, machine learning-assisted (ML) marketing skills for lead synthesis and effective funnelling, alongside the customer need-gauging and persuasion skills of salesmen for gross conversions.
Sales And Marketing: Proxy Warfare
Owing to fear of missing out amidst carrying the burden of justifying investments in the latest digital tools, sales teams feel obliged to react to every customer action and they set up over-optimistic targets that treat every interaction as an opportunity to sell.
Obsessed with customer-centricity initiatives and the restlessness in putting the best of ML-driven journey analytics into effective use, the marketing unit bombards the customers with high-intensity messages, cooked-up greetings and glorified congratulatory wishes and offers right from the start.
The two, in tandem, end up frustrating the customers to the point where they are left with no choice but to mute the notifications and ignore all communications by the enterprise. I call this “over engagement making way for disengagement.”
The sales approach is mostly reactive and all out, while marketing takes the softer route to a larger base in a proactive manner. The sales team emphasizes quickness while the marketing team advocates accuracy. Sales believes that a larger funnel lays the premise for greater conversions while marketing invests its efforts in curating the right funnel for different products with an equal emphasis on pruning leads deemed a misfit.
Common Foes: Haste And Domain Insensitivity
In today’s tech and data-driven era, it is quite common for professionals to change domains. I often come across people who were running the marketing strategies for an ecommerce company not so long ago that are now driving the strategies for banks. Although less prevalent, I have also come across people who were selling telecom devices a couple of years ago who are now selling investment products.
When people change domains, they also carry forward certain skills from their earlier ones. Add to this the noise created by domain-agnostic-software vendors who sell the same products across different verticals claiming there is little difference between sales in different industries.
Enterprises need to strike the right balance between quickness and correctness when acting on leads and assess them through the lens of their domain.
Consider three different leads in different industries:
Quickness on the retailers’ part is paramount toward realizing a sale in Alice’s case, while in the latter two, the quality of recommendations takes greater priority. In Zoya’s case, a few additional hours taken to respond back to her is always worth it when choosing the best portfolio for her needs.
Nudge Vs. Nurture:
While nudging works in all domains, banks hold an edge when it comes to nurturing. Banks should have a clear strategy on which leads to nudge and which ones to nurture. Merely yielding a conversion on leads could have counted as success in the past, but not in today’s ML-driven, strategic lead governance era.
How Banks Can Unscramble the Lead Governance Puzzle?
To start with, banks should consider two things:
They need to go deeper and understand why other verticals have fared better at lead management. They can:
Banks need to realize that they have greater headwinds than other verticals like Telecom or ecommerce when it comes to digital literacy, but at the same time, they also enjoy greater levels of de-facto trust and long-term commitments from their customers.
A new lead is the initial instance of the customer (knowingly or unknowingly) stating their needs to the enterprise. They are also the best opportunities for banks to reinforce trust without adopting an intrusive marketing or sales strategy. Lead governance deserves strategic importance, but it has always stayed in the shadow of either sales or marketing. It is high time for banks to correct the past mistakes and give lead governance the stature and focus it deserves.
This article was originally published here.
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Banks have successfully adopted digitalization to meet the evolving and dynamic customer behaviours. This may sound interesting, but the reality is a bit far from success. Customers are no longer satisfied with the mere availability of digital channels, automation, and self-serve tools to solve their problems. They expect banks to understand and anticipate their financial needs, proactively provide personalized solutions and be more empathetic in their engagement approach. Privacy, security, and trust are the indispensable elements of the banks’ customer-centric engagement approach. In response to the changing market dynamics, a large U.S. multinational bank has revamped its marketing strategy to focus on developing trust and addressing customer needs. The bank aims to rebuild its reputation and strengthen customer relationships by prioritizing transparency and ethical practices.
Let us look at what worked and what didn’t for banks in Marketing in 2023 and the key learning they need to take into 2024 and beyond.
1. Emotions over ease of use
How the customer feels about an experience is more important than the outcome or effectiveness of that experience. Based on a recent survey, feeling valued drives higher loyalty in direct and multichannel banking in the U.S. 87% of direct banking customers stated they would remain loyal to the brand if they felt valued. The trend continues for higher purchasing frequency and advocating for the brand.
2. Data-driven Personalization
Banks and credit unions that effectively harnessed customer data to understand behaviours, preferences, and life events were able to craft highly personalized offers. Capital One leveraged ML algorithms to analyze spending patterns and financial behaviours to provide personalized product recommendations. Another bank employed advanced analytics to analyze customer spending patterns. By identifying customers with high travel expenditures, the bank launched a targeted campaign offering exclusive travel rewards credit cards. The result was a notable increase in credit card acquisitions and customer satisfaction.
mViva’s advanced Analytics and AI-ML capability help banks deliver data-driven personalization at scale. Know more.
3. Omni-Channel Marketing Integration
Seamlessly integrating marketing efforts across various channels provides customers with a cohesive and seamless experience. Many implemented a comprehensive omnichannel strategy, aligning their online, mobile, and in-branch marketing efforts. Customers could seamlessly transition from researching offers on the website to engaging with personalized promotions via the mobile app. This approach not only increased customer engagement but also strengthened the overall brand image.
4. AI-Powered Predictive Analytics
Many have leveraged AI-powered predictive analytics to anticipate customer needs and preferences and deliver relevant and personalized offers at the right time. One medium-sized bank utilized machine learning algorithms to predict which customers would likely seek mortgage loans in the coming months. By proactively reaching out with tailored mortgage offers, the bank not only increased its mortgage portfolio but also fostered a sense of proactive customer service.
Learn more about how to implement AI-powered predictive analytics at your bank. Request for demo.
5. Focus more on educational content
Many companies have invested in educational content to promote financial literacy, which is rising after the pandemic. This has boosted customer loyalty and established trust in institutions that offer informative and easily digestible content.
6. Hybrid model gets the preference
Although the trend suggests digital banking is the future, the data shows otherwise. A hybrid model exceeds the CX score compared to a purely digital or physical model. This shows that human experience still forms an integral part of the overall banking experience for customers.
7. Automation is good when well thought through.
Automation brings a lot of success in terms of cost savings, time to market, resource utilization, and more. Yet many faced challenges due to overreliance on automation. Many financial institutions automated their marketing campaigns but failed to personalize the communication. Many customers were disengaged and frustrated because of impersonal and poorly targeted offers. This led to lower CSAT and a higher opt-out rate from marketing campaigns.
8. Be mindful of Regulatory Compliance
In 2023, some financial institutions faced setbacks due to inadequate attention to regulatory compliance in their marketing campaigns. Violations of privacy and data protection regulations to gather more customer data resulted in fines and damaged customer trust.
Taking the learning from 2023 into 2024 and beyond. What Marketers need to keep in mind when creating a Marketing action plan for 2024.
Marketing is not just about sending offers and promotions to customers. It is an interaction between two parties where each expects to derive value from it. Pelatro’s mViva has been designed to keep this in mind. It helps you bridge the gap between customer needs/preferences and business objectives to achieve the best possible outcome for both stakeholders.
My-Marketing-Muse is a content series started by Pelatro to provide marketers with the latest and best learning in marketing in BFSI. You can follow this series to get regular updates to help you plan your marketing and achieve business goals.
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“Many studies have shown that customer churn can significantly impact a bank’s revenue. According to a study, a 5% increase in customer retention can lead to a 25-95% increase in profits. On the other hand, customer churn can result in losing their current and future business and a likelihood of negative word-of-mouth for the bank.”
While it is difficult to provide an exact figure for the revenue that retail banks lose due to customer churn, it is clear that customer retention is a key factor in maintaining a healthy revenue stream. Banks can mitigate churn by improving customer experience, providing competitive products and services, and implementing effective customer retention strategies. According to some estimates, the cost of customer churn can be as high as 5-10 times the cost of retaining an existing customer. A new-age customer engagement solution will play a crucial role for the banks.
Banks are trying to up their game by modernising their tech stack and infrastructure and adding skilful resources. DBS Bank in Singapore has invested heavily in digital transformation and data analytics to enhance customer experience. HDFC Bank in India has been using advanced analytics and AI-powered solutions to improve customer experience and retention. They have implemented initiatives such as chatbots, voice assistants, and personalised marketing campaigns to engage customers better. Ecobank has implemented initiatives such as mobile banking and digital wallets to provide customers with convenient banking services. Banks also expect increased participation from their tech vendors, such as campaign management and CRM vendors, to help them achieve their business goals.
“Equity Bank and Mastercard in Africa: Equity Bank, a Kenyan bank, partnered with Mastercard to launch a virtual prepaid card that allows customers to make online purchases and pay bills without going to a physical bank.
Ecobank and Microsoft in Africa: Ecobank, a pan-African bank, partnered with Microsoft to launch a mobile banking app that allows customers to check their balances, transfer funds, and pay bills using their mobile phones”.
As we speak of these innovation projects, one solution that is at the core of all this is a campaign management solution. It directly affects the bank’s value creation chain as it is responsible for customer acquisition, engagement, and retention. So, the decision to invest in such as solution should be a thoughtful one. Hence, we have created this checklist for your as CMO or Head of Marketing at a bank to look for when you plan to invest in a customer engagement solution.
12 critical capabilities that retail banks need to look out for when investing in a campaign management solution. Does your CVM tick all the points?
Hyper-personalisation: Banks need a contextual campaign management solution that can personalise messaging to individual customers based on their behaviour and preferences.
Multi-channel support: The solution must be able to manage campaigns across multiple channels, including email, mobile, social media, and website.
Real-time capabilities: Banks require real-time campaign management to respond to customer behaviour as it happens.
Segmentation and targeting: The solution must be able to segment customers based on demographics, behaviour, and other factors and target them with relevant campaigns.
Lead Management: The system should be capable of identifying high-value prospect interaction across channels to ensure a high conversion funnel. mViva can help you exactly with that, and also you can directly push prospects into different journeys from the funnel stages based on their interactions and lead score.
Purpose-driven customer journeys: The solution must enable value-driven customer interactions based on the customer’s purpose, intent and needs rather than just being action driven.
Automation and workflows: Banks need a solution to automate campaign workflows and make it easy for marketers to create and manage campaigns.
Real-time analytics and reporting: The solution must have robust analytics and reporting capabilities to track campaign performance and identify areas for improvement.
Integration with existing and new systems: Banks need a solution to integrate with their existing systems, such as customer relationship management (CRM) and data analytics platforms.
Scalability: The solution must handle large volumes of data and campaigns as the bank grows.
Security and compliance: Banks require a secure and compliant solution with regulations such as GDPR and CCPA.
Ease of use: The solution must be user-friendly and intuitive, allowing marketers to easily create and manage campaigns without extensive technical knowledge.
mViva Customer Engagement Hub offers retail banks all the digital capabilities to provide an integrated experience to their end customers based on purpose-driven customer journeys. The advanced analytics module provides a 360-degree customer profile to execute a segment of one marketing. Banks can offer highly personalised, contextual, and relevant offers in real time, ensuring a high uptake rate.
Re-imagine your customer engagement with mViva.
]]>For example, notifying Susan of the newest arrivals at Prada and Jack of those at Bergdorf as they enter Saks Fifth Avenue was once considered innovative. Today’s algorithms do a lot more work, stitching together even more context to determine if Susan and Jack are moving in together. Or, given their common interest in Italian food, the time of day and a dozen other things, maybe they’re heading toward Armani/Ristorante and need the chef’s menu. This is cool, but what if Susan and Jack begin to wonder, “If something I don’t pay for directly can do all of these things, then what should the banker I invest in be doing for me?” Do bankers have a convincing answer?
Personalization at scale, delivering positive experiences and steering customers toward deeper engagements that lead to a higher share of wallet is the need of the hour—even more so in verticals where customers stay invested longer.
While banking, financial services and insurance (BFSI) and telecommunications companies (“telcos”) have different business priorities, when seen from the customer lifecycle, technical maturity and marketing technology (martech) complexity angles, they are not that different. These are large enterprises offering long-term services to their customers—engagements can easily span several years, if not decades. These enterprises have evolved over time, have stood witness to many tech revolutions (e.g., big data, digital, the cloud), and have rich representation from all of these waves in their IT ecosystem.
Unlike verticals, where lack of data is a big handicap to informed decision making, these enterprises are soaked in data but are largely constrained in their freedom to unleash the full potential due to privacy/consent regulations. They both have millions of customers, hundreds of integrations and billions of events spread across transactional and engagement axes. They are both challenged by newer players, be that neobanks or digital VoIP vendors and risk running into an imminent existential crisis unless they reinvest themselves in their customers’ interests and offer them the most relevant experiences.
Personalization holds the key to relevance, and enterprises are well aware of that. The most important question is whether their personalization initiatives are outcome-driven or experience-driven. To be successful today, enterprises need to go beyond instant gratification.
Pick a telco company or bank—they likely have a string of models to offer tailored experiences by discovering and aligning to their customers’ preferred channels, time for contact, language and even their preferred products. But do they have a sufficient understanding of the purpose and objectives of every single customer? If they did, why is the phrase “segment of one” so common but not “purpose of one?” Outcomes are not created by chance; they are earned.
Enterprises need to look beyond customer transactions and connect to the driving force that is holding them onto the brand. What drives each interaction? Rather than looking at customer activities as a loose combination of unrelated events, enterprises need to take a quantitative approach and sequence the events by tying them along the purpose axis.
Over the past week, say Alice has checked for home loans on a bank website, liked the new credit card promotion on the bank’s Facebook page, re-tweeted the bank’s special home loan offer for public servants, downloaded the banking app and paid the utility bills. It’s messy to group all of these interactions over the recency axis and then try to infer the next-best recommendation for Alice.
Martech of the future should be able to recognize the two strands here—one along the home loan axis and another along credit cards—run through her current portfolio, past engagements, collective interactions with the bank over the last few months and then enumerate all the distinct purposes for which Alice is interacting with the bank and pull them up.
This is called “journey discovery,” a systematic mapping of all of a customer’s engagements—including actions, inactions and silence—grouped over smaller purpose axes, spread along the time axis and then nurtured by aligning them with the enterprise’s business objectives.
When nudges are aligned with customers’ purposes, they translate into desired business outcomes. Customer journey management helps large enterprises, such as BFSI and telcos, realize outcome-driven personalization. Recommendations are provided as long-term prescriptions tailored to help customers meet each of their purposes while aligning with the larger business objectives of the enterprise—not the other way around.
This article was originally published here.
]]>Gone are the days of regular visits to local bank branches for customer service needs to be met. While most BFSI institutions have moved on to dynamic websites, mobile applications, self-serve models and conversational chatbots for multilayered customer engagement, it is pertinent to note that this is only the tip of the iceberg.
The evolution in customer engagement has multiple drivers but can be bracketed into a few that can be considered key driving factors. A primary reason would be a change in expectations of the customers themselves. Today’s customers are influenced by the exposure and experience they receive from OTT, eCommerce and other consumer technologies. With access to immense consumer data sources and advanced analytics capabilities, these organisations can offer hyper-personalisation and instant gratification to customers. For instance, we have seen these tech giants entering the fintech space and disrupting the BFSI sector.
The introduction of neo-banks, fintech startups and micro-finance organisations have also contributed to the disruption and changing consumer expectations. These organisations are creating the perfect cocktail of technology, data-driven product development and hyper-personalised targeted moments-based interactions to elevate customer engagement to the next level. The ones who succeeded work on the age-old model of time=money. i.e., customer time spent engaging has a higher chance of eventually converting to revenue, such as gamification of services.
Digital Adoption, Customer Dynamics, and New Products
To remain competitive and relevant in a space that now includes agile, highly data-driven digital entrants– legacy banks and financial institutions are forced to adapt and delve deeper into customer behaviour by integrating data from multiple channels to be able to provide real-time insights and actions. Banks need to shift to highly customisable and personalised marketing experiences across all channels by pivoting to a customer-centric approach instead of a product-centric one.
The advent of new technologies and evolving customer expectations and behaviour have pushed BFSI institutions, including traditional banks, to find new ways to cater to digitally-savvy customers. But just offering web-based or mobile-friendly interactions is not enough. The self-serve models customised and personalised product recommendations, and moments-based real-time interactions are still distant for bank customers.
This would require leveraging real-time behavioural and transactional data to create a potent customer knowledge base. A rich customer knowledge base with the appropriate platform can predict when to reach out to customers and which product or service they would be interested in. Essentially, when the appropriate martech ecosystem is adopted, the bank or financial system can predict an individual customer’s needs and reach out at the right time with the right product or service. A customer who has a saving account and a credit card with XYZ bank but has a loan from another bank can be approached with lower interest rates based on their credit score/history.
With ever-growing amounts of data entering the system and the use of emerging technologies such as artificial intelligence combined with intuitive marketing technology platforms, BFSI organisations can have highly customised touchpoints with their customers.
For example, loyalty programs enhance customer experience by instantly gratifying customers through rewards, offers and discounts. This is especially important for legacy BFSI institutions as trustworthiness and personal relationships are two of their strengths, with new marketing technologies now providing the option to continue maintaining their advantages while going digital.
Artificial intelligence in BFSI has massive potential for growth, and the institutions that are quickest to draw will likely gain a huge competitive advantage. These organisations will be able to improve operations, drive customer engagement, optimise experiences, and automate insights to act on, in addition to providing services like conversational chatbots, portfolio optimisation, enhancing credit decisions, and strengthening cybersecurity.
AI & ML can segment customers based on dynamic parameters, increase product or service adoption by using micro-segmentation and providing context-based offers on a real-time basis and enhance cross-selling or upselling.
An AI/ML-enabled martech solution can allow BFSI institutions to:
Additionally, A well-thought and structured approach can take advantage of having a single source of data across the disparate functional areas of the business (for example, the loan department). This would allow the martech tool to analyse individual customer profiles holistically, enabling the AI engine to recommend offers with a higher chance of acceptance.
Banks and other non-banking financial institutions are aware of the risk of losing customers to more customer-oriented, digitalised and data-driven institutions. This primarily concerns the competitor’s ability to engage, retain and activate their customers.
The solution lies in advanced analytics. The BFSI sector needs to be able to use data to predict sales trends, identify and act on customer sentiment, identify and act on risks in advance, and segment customers in a manner that allows them to target high-value customers for greater returns specifically.
As per this article, advanced analytics works best based on five principles – segmenting customers, automating forecasts, predicting loyalty, understanding the causes of churn, and a test-and-learn approach.
Most institutions probably do so based on demographics (age, gender, income, etc.), which is useful but ignores the nuances of the individual. Demographic-based segmentation of customers inherently includes the assumption that the group is homogenous in nature.
The right martech ecosystem that provides advanced analytics will be able to provide the reasons behind a customer’s behaviour. Why did customer X choose a product from a competitor? Similarly, advanced analytics of data can help a bank predict whether a customer will remain loyal or not (and why).
As discussed above, the future of marketing in BFSI looks interesting with the advent of advanced martech solutions that offer the best of capabilities. But is that the only correct approach for all BFSI marketing problems?
It’s not that easy! The significance is to recognise that a martech solution is ever-evolving, and organisations should look to ensure that their customer’s profiles and personas are continuously updated. Sources like first-party cookies allow banks to upgrade their customers’ personal data, thereby improving future journeys. The right technology platform will then allow the bank to enhance the user’s experience and amplify engagement in real-time.
The use of AI & ML, when paired with the right technology, can ensure that institutions can improve targeting accuracy, provide much greater value to customers and, in turn, increase revenues. For example, AI and ML use cases may include financial monitoring, investment predictions, process automation, secure transactions, risk management, algorithmic trading, financial advisory, etc.
Another value-added service that banks can offer to their customers is by using customer behavioural and transactional data to provide real-time contextual promotions. For instance, a bank could partner with retailers and access geospatial data to push promotions to customers who have visited the store (physically or digitally) and are currently in the vicinity. This provides added value to the customer, which in turn, enhances customer loyalty.
It is salient to remember that competitiveness in the BFSI sector is increasing, reflected by the ever-rising share of marketing budgets invested in the digital domain. Financial institutions must find ways to be unique, with the best performers being those who prioritise providing value to customers over product sales.
Want to know how mViva can help you? Download our mViva for Banks flyer.