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How Red River Digitized End-to-End Customer Engagement to Create Customers for Life


August 26, 2016 - 3 Comments

Creating customers for life is fast becoming the ultimate goal in our industry, and it’s a core mission for Cisco, too. That’s why it’s always inspiring when we see our technology partners put the customer experience front and center in their businesses. Red River is the perfect example. As a technology integrator and Cisco Gold Partner, the company is best known for its focus on the U.S. government, and for delivering technology solutions and services to military and civilian agencies and the organizations that serve them.

Like other technology sector businesses, Red River has seen the customer landscape turn increasingly digital, with customers performing the majority of their sales research—along with a greater number of transactions—online.

Less face time means less stickiness with the customer, which is why Red River has moved to adopt more relevant business strategies to compete more effectively in the digital economy.

In October 2015, it began participating in the Cisco Lifecycle Advantage program to create valuable touch points across the entire digital journey – from the point of sale, to product and service adoption, to service and subscription renewals, and beyond. Because Lifecycle Advantage is 100 percent data driven and built on analytics, Red River is assured that these touch points are on the mark, allowing them to reach out to the right customer, at the right time, with the right message.

 

How does Lifecycle Advantage help Red River flow? Watch this video for an inside perspective.

 

Data Mining for Opportunity

Through Lifecycle Advantage, each month Cisco mines its data repositories to provide Red River with a clean list of service renewal opportunities. Using highly scalable email automation capabilities, Lifecycle Advantage allows the company to quickly execute on these renewals along with other expand selling opportunities.

The numbers tell the story best: in the last six months, Red River increased its service renewal rate by 35 points year over year, achieved a 60% increase in service renewals and increased services bookings by 142% year over year. Lifecycle Advantage played a role in this impressive growth. If that’s not enough, email open rates throughout the Lifecycle Advantage renewal campaigns have doubled, and email click-through rates have tripled, providing proof points of the program’s reach.

Red River is focused on creating value across the full lifetime of the customer relationship, and earning the privilege to expand business with existing clients through recurring revenue programs such as service renewals. As the foundation of Lifecycle Advantage, data is not only vital for making all of this possible, but also essential for helping Red River execute on its goal of creating customers for life. We couldn’t be more proud of their success!

To find out how other industry leaders are using data to realize their goals, visit the SuccessHub.


“At Red River, we understand the customer life cycle, and that it’s not enough to take an order and walk away. Lifecycle Advantage has been especially helpful in making sure our customers renew on time. This has always been a goal for us, but since using Lifecycle Advantage we’ve been able to execute on that goal more successfully. Our customers also now understand we’re working together with Cisco to make sure their technology assets are protected with service agreements—which has significantly improved customer satisfaction.” – Senior Support Executive, Red River


 



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3 Comments

  1. I hope it is really a great idea of remembering customers regarding their expiry of policy renewal, Even though Lot of process are there to accomplish this type of work in a market it will create a niche in CRM.

  2. Definitely, Data mining (DM) is the name given to a variety of computer-intensive techniques for discovering structure and for analyzing patterns in data. Using those patterns, DM can create predictive models, or classify things, or identify diff erent groups or clusters of cases within data. Data mining and its close cousins machine learning and predictive analytics are already widely used in business and are starting to spread into social science and other areas of research. A partial list of current data mining methods includes: . association rules . recursive partitioning or decision trees, including CART (classifi cation and regression trees) and CHAID (chi-squared automatic interaction detection), boosted trees, forests, and bootstrap forests . multi-layer neural network models and “deep learning” methods . naive Bayes classifi ers and Bayesian networks . clustering methods, including hierarchical, k-means, nearest neighbor, linear and nonlinear manifold clustering . support vector machines . “soft modeling” or partial least squares latent variable modeling DM is a young area of scholarship, but it is growing very rapidly... Definitely a great tool as applied by Red River...Thanks for sharing this interesting article.

  3. Thanks Kelly.