How MarTech enhances the marketing abilities of brand marketers?
Brand marketers today face a challenge of capturing the attention of an audience in a world that has distractions increasing by the second. In such an attention deprived world every interaction that you have with your customers needs to be personalized and memorable. That’s where MarTech comes as a great enabler.
For businesses today, delivering hyper-personalized and contextually engaging campaigns are the assured way to capture the attention of customers.
Marketing automation connects the dots of 4R’s i.e. reaching the Right person at the Right time using the Right channel with the Right content.
By effectively leveraging the power of artificial intelligence (AI) and machine learning (ML), marketers can establish an accurate and reliable predictive foundation for multi-channel engagement based on historical customer behaviour, actions, and inactions. Intelligent human intervention will help ‘martechers’ recognize and appropriately harness the hidden patterns and trends facilitated by this technology.
What is the importance of customer data platform in marketing?
Knowing your customer is the first step towards building meaningful engagement with them. The more you know, the better equipped you are. You need to collect data from all the touchpoints possible and present it in a unified view to paint the right image of your customer and that is exactly what a CDP does.
A CDP is a persistent and unified customer database designed to collect and organize customer data across all interactions and attributes. This data is available to systems across the organization for action and analysis. CDPs approach data from a centralized customer profile perspective and all the real-time data is organized adhering to the approach. The CDP contains individual identifiers used to target promoting messages and track singular level results.
It is very different from a CRM wherein you manually enter the data related to your customer via the intended interactions. A CDP collects data in an automated manner from both online & offline channels directly from the customers (even for anonymous visitors), does modelling on the acquired data, creates a lifetime customer behaviour & journey and helps the marketer analyse and derive actionable insights via a unified view. All these functionalities make a CDP different from a traditional CRM and a DMP. According to Gartner, data collection, profile unification, segmentation and activation are the basic functionalities that all CDPs intend to provide.
Today, just knowing the target segment isn’t enough. Personalized communication to each of your customer is a mandate. And the first step to personalization is building a CDP. Benefits of a CDP include cross-channel attribution (Personalization, Customer Insights, Measure across Channels), agility and future ready infrastructure and democratization of data.
The demand for omnichannel experience and actionable insights makes Customer Data Platform a must-have in today’s MarTech space.
What’s the role of personalization in providing better customer experience?
According to Frost & Sullivan, customer experience will overtake price and product as the key brand differentiator by 2020. Audiences demand personalized brand interactions and this is the driving force behind the rapid growth of personalization.
As per Gartner, organizations who focus on personalized messages for customer interactions can expect 16% more impact on commercial outcomes compared to those who don’t. Even the Gartner Hype Cycle for Marketing & Advertising, 2019 emphasized on the continuation of the rapid growth of CDP & Personalization engines.
Personalization engines create a relevant, individualized interaction between two parties designed to enhance the experience of the recipient. Most engines do not only help orchestrate multichannel marketing, but also customize digital commerce experiences through personalized product and offer recommendations, search engine optimization (SEO), site search & navigation. Thus the persistent data and its unified view via a CDP become so important for personalization.
Today, the best personalization engines personalize each customer interaction across multiple channels i.e. web, mobile web, mobile apps as well as email. Taking up an example, today when a customer logs in to an e-commerce website or an app, the entire page is tailor made and personalized according to that very customer. The brand shows her only what she wants to see and finds relevant — starting from the headlines, product/service categories, the recent updates on products and offers, suggestions/recommendations (depending upon the customer’s last purchase or wish-list), complimentary products (depending on the items in the cart) and even taking the customer to her preferred transactional channel. Even if the buyer drops off at any stage, personalized emails or notifications are sent by the brand which enables the buyer to carry forward from the very step where she left removing the hassle to go through the process again.
This is the level of personalization that the brands are keen to offer; be it on web, apps or emails. The customer finds a seamless experience from the very first step to the checkout step which results in increasing customer experience and brand loyalty. Personalization engines use insights based on the recipient’s personal data as well as behavioural data. So the brands interact with the customer the way the customer wants and with the communication the customer wants. Thus, marketers answer the big question of ‘customer experience’ with ‘personalization’ as their tool.
How has been the adoption rate of MarTech in India?
The blend of Marketing and Technology, MarTech is growing rapidly and has attracted a huge chunk of the Indian companies. The MarTech adoption in India keeps on growing with every day as brands realize the huge potential of the space and also need efficient and advanced technology advancements to handle the humongous data and to interact with the right person with the right content via the right channel at the right time.
Forrester projections show that global MarTech spending was projected to hit $13.4 billion in 2018, a figure that will nearly double to $25.1 billion in 2023. With the rise of more and more technological advancements in marketing, the Indian market has also strapped its boots as far as MarTech adoption is concerned. As per Nasscom, MarTech is a $45-55 billion opportunity for the Indian IT industry.
In India, the rise of contextual marketing and the convergence of MarTech and AdTech have ensured that marketers spend a good chunk of their budgets in this area. The tech-savvy Indian audience and the recent success of good technology products mean that MarTech continues to be hot and grow further as far as the Indian market is concerned.
What are some of the major global trends in MarTech?
- CDP: A CDP is a software that collects the customer data across channels from different marketing campaigns in order to provide a unified view of the customer. Data collection, profile unification, segmentation and activation are the basic functionalities that all CDPs intend to provide.
- Personalization: Personalization engines create a relevant, individualized interaction between two parties designed to enhance the experience of the recipient. They use insights based on the recipient’s personal data as well as behavioural data. Today, the best personalization engines personalize each customer interaction across multiple channels i.e. web, mobile web, mobile apps as well as email.
- ML & AI: Machine Learning and Artificial Intelligence continue to be the two big buzz words in the MarTech space today and all the players realize their potential. Building capabilities to leverage their functionalities remain in the roadmap for all. As per the Gartner Hype Cycle 2019, these capabilities have reached the peak and are going to disrupt the tech market the most in the coming years.
- Predictive Analytics: Predictive analysis helps to find actionable insights from huge chunks of customer data by using ML and modelling techniques. To use the enormous data in the correct manner to derive meaningful outcomes and predict the future in the addressed channel. Using predictive analytics, brands today are able to communicate at a very advanced level by offering the next best step/offer which is personalized as per the individual customer.
- Augmented Analytics: Augmented analytics leverages Machine Learning & Artificial Intelligence techniques to transform analytics’ content development, consumption and sharing. The growth of augmented analytics is correlated with how effectively and efficiently the brands use AI. According to Gartner, ‘Augmented Analytics” are among the top trends that have significant disruptive potential over the next 3 to 5 years.
- Event-Triggered & Real-Time Marketing: Event-triggered functionality involves the detection, prioritization and execution response for significant events which affect a brand’s relationship with a customer via different modes of interaction. Real-time marketing refers to the brand interacting with its customers based on data reported instantaneously which means that marketers can make decisions and respond to customers with their needs at that very moment.
Netcore, being an established player in the MarTech space, realizes the enormous potential of these trends and have already started implementing them. ‘Raman’ is the name of our AI/ML engine designed to bring the power of AI & ML to the capabilities of Netcore’s flagship offering Smartech – the cross-channel marketing automation and actionable analytics suite, Pepipost – API-based email delivery platform, and advanced Analytics solutions.
Following are the ways in which Raman benefits marketers:
- Using Netcore’s Smartech
- Using Netcore’s Pepipost
Raman helps improve the email delivery throughput with better ‘primary’ inboxing rates. This gives a big boost to the overall campaign performance.
- Using Netcore’s Analytics
Analytics is a crucial tool for marketers looking to understand and orchestrate hyper-personalized customer journeys. Raman augments analytical capabilities with its predictive algorithms by helping marketers to find new sets of customers similar in profile to their high-value ones and win back churned out customers through effective re-targeting. It also helps marketers to increase profitability by nurturing existing customers through Customer Lifetime Value Prediction.
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