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5 Ways Machine Learning Increases Marketing Performance

Strong marketing performance is dependent on data analysis and customer insight. But often marketing needs to wait for business intelligence and analyst teams to produce insights, models, and segmentation before they can act. And, models need to be updated 2-3 times per year. This leaves marketing working with “out of date” insights that don’t account for the latest customer behavior or channel preferences. In an on-demand customer driven environment, “out of date” insights hinder marketing’s ability to increase, or even maintain, campaign performance.

Increase Marketing Performance with Real-Time Data Analysis

There is a lot of chatter across the marketing industry about machine learning. The truth is machine learning is an advanced tool that enables marketers to leverage real-time data for greater insights. It, quite simply, solves for problems using patterns we cannot see. It helps us drive increased marketing performance by giving us access to real-time data analysis that we humans do not have the capacity to compute.

1. Better personalization

Machine learning will rapidly analyze and learn from high-volume, varied and detailed data — whether structured, unstructured or semi-structured. This increases our ability to segment the customer into segments of one, at scale. The ability to personalize specific recommendations and next best offers, and deliver them in real-time, allows us to lead our customer more reliably through their journey. The result? Increased revenue.

2. Better customer service and support

Machine learning recognizes patterns in customers’ past engagement and actions. By doing so, it helps us know who they are and how we can best support them on their journey by interacting with them at the appropriate time and in whatever channel, with messaging and actions personalized to them. According to Forrester Research, customers will pay more for a better experience. The personalized experiences you create are welcomed by your customer. That customer is now more likely to engage further with your company, increasing the probability of greater loyalty. Your customer lifetime value increases along with customer satisfaction.

3. Increase relevancy

Machine learning customer segmentation models can be used very effectively to increase relevancy. They can segment customers into small, homogeneous groups who have similar behaviors and preferences. This allows marketing to create greater relevancy by delivering messaging that are in sync with customers’ preferences and wherever they are in their lifecycle. This translates to being able to steer customers more accurately through their lifecycle to a positive action.

4. Increase conversion

Machine learning’s ability to provide predictive analytics increases the likelihood a customer will convert by supporting real-time interactions across multiple channels.

5. Forecast customer lifetime value

By finding patterns in past customer behavior and optimizing our analytics machine learning helps us predict a customer’s journey and thus their lifetime value. This improves efficiency in resource allocation, campaign management, and ROI forecasting.

With machine learning we can adapt and evolve our strategies and campaigns quickly, and accelerate our ability to interact with each customer by using all our data efficiently and effectively. To find out more about how to take advantage of machine learning to increase your marketing effectiveness download our newly published eBook; The Value of Context, Cross-Channel, and Real-Time Capabilities: Advancing Marketing’s Productivity.

About VeraCentra:  Marketers everywhere want to use data to implement more modern customer engagement strategies. But there can be many obstacles standing in the way of success. That’s where we come in. VeraCentra provides easy-access Customer Data Hubs. We represent best of breed Cross Channel Engagement Platforms (so marketers get the right fit) and offer the Marketing and Data Services that guarantee speed to value and quick win ROI from technology investments. We deliver these solutions with an unmatched wholehearted approach bringing personalized support, care, and service to every client. That’s why many of our client relationships span more than a decade.

 

 

Machine Learning and Real-Time Customer Interactions

Customers are interacting with us in real-time and we need to do the same.  We know we need to respond faster, but accessing and analyzing data across channels is cumbersome and painfully slow. And, it just doesn’t cut it in real-time world our customers live in. And the workarounds we put in place to compensate for our silo data are too slow. They make it impossible to deliver the real-time customer interactions needed to drive customer loyalty.

Machine Learning Picks up Where Basic Analytics Fall Short

Making full use of our data is paramount in today’s competitive environment. It is difficult to do so if we are having to create models offline and manually consolidating multiple centers of truth.

Additionally, we need to develop insights from data assets faster and with greater precision, which in turn enables us to develop competitive marketing strategies designed to drive customer loyalty.

With limited time and resources, legacy systems, and multiple partners and channels to contend with machine learning picks up where basic analytics fall short.

How to get started

Delivering relevance at every touch point, in real-time may be too big to bite off all at once. Take a phased approach. Start with getting your data in order. Inventory it and gather it in one central repository for a complete view of your customers.

You need to invest in a Customer Hub to bring order to data organization, cleanliness, and accessibility. Centralizing marketing data across the organization will create the one center of truth you need, pull your teams together, and will do so without having to consolidate partners.

Invest in the right technology to deliver relevance at scale, across all channels and devices. Machine learning can help predict the next step in the customers journey no matter which channel and device — it connects the dots online and offline… from web browsing to face to face interactions.

The Future

Technology, and with it machine learning, is growing and evolving quickly. Creating competitive advantage now relies on having the capability to consolidate our data into one center of truth and leveraging machine learning tools to deliver the real-time customer interactions required to stay ahead.

To find out more about how to advance your real-time capabilities with machine learning download our newly published eBook; The Value of Context, Cross-Channel, and Real-Time Capabilities: Advancing Marketing’s Productivity.

About VeraCentra: Marketers everywhere want to use data to implement more modern customer engagement strategies. But there can be many obstacles standing in the way of success. That’s where we come in. VeraCentra provides easy-access Customer Data Hubs. We represent best of breed Cross Channel Engagement Platforms (so marketers get the right fit) and offer the Marketing and Data Services that guarantee speed to value and quick win ROI from technology investments. We deliver these solutions with an unmatched wholehearted approach bringing personalized support, care, and service to every client. That’s why many of our client relationships span more than a decade.