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Why have CDPs caught the fancy of Indian Mutual Fund Marketers?

Why have CDPs caught the fancy of Indian Mutual Fund Marketers?

Being a Marketer for a Mutual Fund or an Asset Management company can be complicated. It’s easy to get into a panic state with ever-changing regulations and constant policing by compliance teams. In short, the life of Mutual Funds Marketers is not as easy and liberated as their peers from Retail or CPG. However, the evolution of Marketing technology has come to the rescue of such Marketers. Be it Data Privacy compliance OR be it the Monthly Recurring Fund update, Technology has taken care of it and brought in some relief. Interested to know which Technology are we referring to?? This new technology on the block that is making news is nothing but a Customer Data Platform. It is enabling Marketers to automate recurring compliance-led campaigns and tons of other things that they are unable to otherwise do with their existing Campaign tool. What is a Customer Data Platform? How different is it from a Marketing Automation Platform? Is it the same as CRM or a DMP? What is the strategic importance of a Customer Data Platform to a Mutual Fund Marketer? It is very natural for you to have these questions if you are new to Customer Data Platforms and thus we have answered all these queries in our blog here. Customer Data Platform as defined by CDP Institute is packaged software that creates a persistent, unified customer database that is accessible to other systems. In simpler words, a Customer Data Platform(also known as CDP) helps enterprises achieve a Single Customer View by ingesting every customer interaction that takes place in any form and on any channel. Be it a voice call dialed to a Customer Care, transaction done in a physical store, or a comment on a social media post, all interactions are ingested by CDPs to arrive at Single Customer View. And this Single Customer View helps the brand to know more about the customer and thus engage better with more relevance. Well, the story doesn’t end here… While most of the CDPs conclude their offerings at Customer Unification, there is a full-stack or a comprehensive CDP like FirstHive that enables Marketers with much more than a Single Customer View. And one of those differentiating features of FirstHive is efficient campaign execution capabilities. What would be your reaction if someone comes and tells you that we will reduce your campaign execution time and effort by 90%?? would you be Happy? Sad? or Excited?… Come, let us introduce you to Hyper-Personalization, a technology that is not just another buzzword but a rescue engine for Marketers. What is Hyper-Personalization? Hyper-Personalization is an advanced technology that enables Marketers to personalize campaigns beyond the general ‘Name’ personalization and can also factor in aspects like preferred content (Not just text but also images…Yes, images, you heard it right), preferred time, and preferred channel. And the reason why Hyper-Personalization is way more critical to Mutual Fund marketers as compared to their peers is because of the potential it carries to reduce their time and effort by 90% which otherwise they would have invested or rather wasted in the execution of recurring campaigns that are more compliance-driven than marketing-driven. And yes, this definitely means that you will be left with more time and resources in hand to think about ways to upsell, cross-sell, acquire customers, retain customers, and everything that would satisfy the marketer in you. How does Hyper-Personalization reduce the time and effort of a Mutual Fund Marketer? There are various use cases of Hyper-Personalization for Mutual Fund companies however let us list them in the order of criticality, starting from the most critical one. Let us understand each one of them in detail. Sending FactSheet to all customers every month Upselling or Cross-selling basis Fund performance Personalized experience to customers on other channels Reduce Time to Value via Partner Engagement model Sending FactSheet to all customers every month Let’s say you have 12 different funds. Today, are you sending 12 campaigns every month or is it just one?? If you are still sending 12 campaigns, then it is a perfect opportunity for you to learn about how FirstHive CDP can reduce that number to one campaign. FirstHive allows you to set conditions for content display that too for content in all forms – Be it Text, Numbers, Alphanumeric, Date, Images, or even URL. This process also called ‘Content Mapping’ is a very simple process of setting conditions offline in an Excel format which you then upload in one campaign so that the system derives 12 content drafts from one email draft thereby reducing your effort in creating another 11 drafts of emails. In short, by executing one campaign, you would be delivering 12 different content email campaigns. Woah!! What are you waiting for?? Upselling or Cross-selling basis Fund performance As per law, you do send a FactSheet to every customer but in that same email, basis the fund performance, do you communicate something more… For example: If the fund has done well, ask the customer to top-up his investment or if the fund has not done well, showcase other performing funds and widen the customer’s portfolio. FirstHive enables you to set rules in the content mapping section in a way that different content is pushed to the customer basis the fund performance. This ensures that the customer won’t just receive the Fund Performance details every month but also enough guidance on what to do next. And as you can imagine, this slight change in approach can bring dual benefits to the brand – One is that the Customer will feel BETTER engaged and not OVER engaged, and the second is that the sales will increase as a result of razor-sharp targeting. I mean, along with sharing the factsheet and telling me that my fund has done great if you are also pushing me to click on a button and invest more, there are higher chances of me clicking that button because the premise is that I would be in a happy state of mind. Wait…isn’t this ‘Marketing in Moments’ as stated by Forrester Analyst Joe Stanhope. Well, not bragging… but it is 🙂 Personalized experience to customers on other channels CTA of a mutual fund campaign typically is a Click that takes the user to the website or a landing page. But thereon, does the website or landing page show personalized content to every user of that campaign, or does the entire audience of one campaign land on a webpage that showcases the same content to everyone. Hoping it’s not the latter. In case it is, it is.. i.e; all users of one campaign see the same content on the landing page, it’s high time you start practicing Hyper-Personalization. In this era of Netflix where you as well as your customers have got used to seeing personalized recommendations, showing all of them the same content on the page is quite a passe. I bet, you will agree.  Reduce Time to Value via Intermediary/ Partner Engagement  Most of the Mutual Fund companies work around a Distributor model wherein Mutual Funds are sold via IFAs. These IFAs obviously have a strong network of investors, they maintain a good hold on their investments and play a big role in their buying/ selling decisions. Then why not target these investors via IFAs. This is exactly what Partner Engagement is… i.e; communicating in the line of Mutual Fund-Distributor-Investor. In simple words, it is a method in which you are targeting end investors of IFAs via IFAs but without letting the control go out of your hands. By control, we mean, the control from Marketing’s perspective i.e; Branding, content, time of execution. FirstHive’s Partner Engagement model lets you design the campaign in a manner that the Campaign would be delivered to the end investor via IFA’s branding as well as via the IFA’s email id in a manner that your brand aesthetics are maintained and the content is personalized. Wait, not just this… the icing on the cake is that the IFA would get real-time access to his investor’s response to the campaign. And the response would not be just another generic response like Clicked or Opened but it would be something as crisp as – “Eric John went to the website and explored the XYZ fund that we recommended”. Yes yes, you are reading it right…This means that the Mutual Fund house will share high intent data with the IFA which will not just increase their Sales but also strengthen their bond with the IFA. And that’s precious. Isn’t it?? So here we come to an end with all Hyper-Personalization use cases we thought would be relevant to you as a Mutual Fund marketer. If you are excited about what you just read and are keen to see this in real, please Click Here. Lastly, an important point to note is that FirstHive is a resilient product backed by Amazon Web Services (AWS) to strengthen its architecture. Besides Amazon Elastic Compute Cloud (Amazon EC2) that offers highly scalable infrastructure, FirstHive also uses Amazon Relational Database Service (Amazon RDS) that stores billions of row of data with an above industry uptime, AWS Transcribe service to convert voice data of customer interactions into searchable & analyzable digital content and Amazon Sagemaker platform to train machine learning models & generate the intelligent inferences. The Hyper-personalization functions run on Amazon Elastic Container Service (ECS) that is capable of elastically auto-scaling based on the varying business needs, while image recognition capability of Amazon Rekognition is leveraged in different types of sentiment analysis. P.S: And yes, do read our blog Unmasking differences between Customer Data Platform and Marketing Automation Platform and DMP Vs CDP Vs CRM

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Auto-Segmentation — The smart way of mastering Customer Segmentation

Auto-Segmentation — The smart way of mastering Customer Segmentation

‘I wish this customer just thinks straight.’ And that never happens. Thinking patterns conflict, coincide and converge each other. As a marketer, prevalence of multiple thinking patterns emerging out of your customer journeys bothers you.  Just like there is more than one way to reach your office from point A, there are many ways in which a customer ends up discovering your product and decides to purchase it. What you fumble as a marketer is to predict paths that customers choose. It gets even more complex when customers start exploring more than one channel to evaluate and engage with your brand.  It is beyond human thinking to imagine all possibilities that can segment existing and emerging customers.  SQL tables and IT tickets SQL tables brought some order to the madness. They have been able to organize raw data and nothing more. IT ticketing systems were the next step to the evolution of customer segmentation. But, neither of them gave any real-time insight, weighing the larger picture.  They threatened businesses with the lack of data privacy. Tools like SQL tables and tickets could not store data in an authentic way. Customers shied away from brands that misused their private data. Poor management of private data and lack of an intent to establish transparency translated into leaving the platform or abandoning the product. For marketers, it was not being able to efficiently filter data. The mediocre data could not be used to identify target audience and target real campaigns. While marketers are grappling to find a single solution, we have it sorted for you. Automating the process of segmentation customers into comprehensible and manageable segments is the problem that we are addressing in this article, below. One of the most sought after features in a CDP for audience segmentation is the auto-segmentation that is available in FirstHive. Explore Auto-segmentation “How can Marketers master automation of customer segmentation?” Customer segmentation is a process that is now collectively done by marketers (humans) and technology tools (machines). This brings us to define auto-segmentation. Auto-segmentation is the process of segmenting customers into cohorts that fulfill a certain criteria by leveraging machine learning that can provide recommendations over the system, beyond demographic attributes and transaction history. We deploy powerful algorithms that involve k-means for clustering cohorts. To automate the cohort segmentation process we rely on unsupervised machine learning. While this sounds simple, the complexity increases when you are mapping your cohorts using a criteria that has more than two or three dimensions. FirstHive applies the auto-segmentation to realize real cohorts that can be used to construct fruitful campaigns.  In the campaign activation module, these customer segments could be selected for implementation. During live campaigns, customer segment cohorts are automatically updated. This adds more efficiency to the campaign optimization process too. It also enables automation of altering triggers that control campaigns. Apart from automated updates, the algorithm also recommends. There are two layers to the recommendations made. The customer segment recommendations are made to marketers. And, the segments are also enabled to make product and content recommendations directly to the customers within different cohorts. Thus increasing relevance. Visual representations validate and augment the recommendations determined by the algorithm. This also means that you not only promote and focus on the high performing customer segments, but find out those negative audiences that are not contributing or hurting your business. It is assumed that customer segmentation is to segregate audiences by geography, demography and transaction value plus behavior. But, it is more. A marketer needs to analyze deeper into customer behavior and personality using many dimensions. Engagement channel preference, first touch point, product preference, content subscription are few other parameters that could be applied to build cohorts. Auto-segmentation combined with recommendation systems brings forth many advantages.  Finds hidden clusters within the dataset that represent important customer segments.Remains devoid of errors that are caused by human assumptions. Automation ensures scalability and productivityIndividualized personalization can be achievedDatabase and customer information is kept up-to-data, round-the-clock. To enjoy any of the benefits, email us at marketing@firsthive.com and discuss how you can automate your customer segmentation process. 

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One size doesn’t fit all: Everything that you should know about Customer Segmentation as a Marketer

One size doesn’t fit all: Everything that you should know about Customer Segmentation as a Marketer

Have you ever stepped into a store’s trial room feeling very comfortable in clothes that don’t fit you? I guess that would not happen. It’s the same scenario while validating the need for customer segmentation. It’s been estimated that marketers who send segmented campaigns see as much as a 760% increase in revenue.  There are more reasons why customer segmentation is a must-have in your marketing strategy. What is Customer Segmentation? Customer segmentation is a process by which customer data is classified into similar groups to achieve a common objective. Segmentation can happen based on demographic data, psychographic data, behavioral data, geographic data, customer journey data, and many more.   Customer segmentation helps marketers target a specific group to achieve a specific result. Such close targeting optimizes the money spent. Without customer segmentation, you may end up sending the wrong message and selling the wrong product to the wrong group of people. Intuition is not enough: Why is it important to segment customers? Segmentation is based on proven data. That means it leaves no room for guesswork. While being intuitive is awesome, you need data to back your decisions and device-relevant campaigns that convert well.   Reach out to a diverse audience with the same need for your product. Optimize budget spending to get the most out of a homogenous group of the target audience. Create a better brand resonance. Surface promising or untapped business opportunities Understand the most and least engaged customers at a granular level.  To achieve granular segmentation, you need to use an exclusive combination of dimensions and parameters. Such a combination is relevant to the objective of the campaign. This helps us to understand different types of customer segmentation. Types of customer segmentation As mentioned earlier, some of the common ways to segment customers are based on data coming from demographics, psychographics, geography, behavior, and customer journeys. Demographic segmentation Demographic segmentation is when customers are categorized by certain socioeconomic factors, such as:  Job title Age Gender Religion Marital status Social security number Urbanization Psychographic segmentation Psychographic segmentation looks at the attributes and characteristics that form our personalities. A common example is buyer personas, which create imaginative backstories about potential customers (combining demographic data, like job title, with more psychographic data like motivations, preferred method of communication, and so on). Examples of psychographic segmentation include:   A person’s interests  Values Opinions  Habits  Buyer preferences Motives Geographic segmentation Geographic segmentation is when consumers are organized into groups based on their location. This could be as broad as a region (e.g. North America) or a specific city (e.g. Boston). Geographic segmentation can be done by:   Country Time Zone State City  Zip code IP address Dynamic location Behavioral segmentation Behavioral segmentation provides insights into how a person chooses to engage with your business. Some examples of criteria for behavioral segmentation include:   Pages viewed Requesting a demo Items that were added to the cart Cart abandonmentCompleting a purchase Customer Journey Segmentation  Customer Journey segmentation is based on which point or place of journey the prospect or customer is going through. For eg:  Discovery and Search Pre login Post login Referral coupons Word-of-mouth referral Competitive comparison What do you do with Customer Segments? Some of the most common use cases that use customer segments as a foundation is as below:  Personalization of marketing campaigns and product experience Product usage and product development enhancements Raw data and inputs to make new business decisions Customer-product fit Product-market fit FAQs What is the purpose of customer segmentation? Customer segmentation helps you gain unique insights about a specific target group. It helps marketers gain a deeper understanding based on the segregated dimension and common parameters. Customer segmentation allows businesses to better connect with customers by tailoring their communications, with the added benefits of improving customer experiences, optimizing ad spending, and more. How to define customer segments?  Build a criterion to meet your objective. Define which type of dimension you want to use. Slice the segment based on different categories: demographic (e.g. a person’s age, gender, etc.), psychographic (e.g. interests, beliefs, and personality of an individual), geographic (e.g. where a person lives),  behavioral (e.g. the actions a person has taken with your business), or customer journey (before login, after purchase, while check out and so on). Can customer segmentation be automated? FirstHive’s Customer Data Platform is built on machine learning algorithms that are applicable to customer segmentation. The platform can auto-segment into intelligent cohorts that come as recommendations to the marketer who is using the system. These segments can also be fed into the campaign automation system of your choice. These segments come as enriched data inputs for the campaigns to be executed in real-time.

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