segmentation

10月 142020
 

Everything happens somewhere, and much of our customer data includes location information. Websites include x, y coordinates in semi-structured click streams, and the mobile apps your prospects depend on frequently support device location to provide a personalized, targeted experience. As my SAS peer Robby Powell said: "Human brains are hardwired [...]

SAS Customer Intelligence 360: Data visualization, location analytics and geospatial insights was published on Customer Intelligence Blog.

3月 122020
 

In parts one and two of this blog series, we introduced hybrid marketing as a method that combines both direct and digital marketing capabilities while absorbing insights from machine learning. According to Daniel Newman (Futurum Research) and Wilson Raj (SAS) in the October 2019 research study Experience 2030: “Brands must [...]

SAS Customer Intelligence 360: Hybrid marketing and analytic's last mile [Part 3] was published on Customer Intelligence Blog.

9月 032019
 

In part one of this blog series, we introduced hybrid marketing as a method that combines both direct and digital marketing capabilities while absorbing insights from machine learning. In part two, we will share perspectives on: How SAS Customer Intelligence 360 completes analytic's last mile. How campaign management processes can easily [...]

SAS Customer Intelligence 360: Hybrid marketing and analytic's last mile [Part 2] was published on Customer Intelligence Blog.

8月 262019
 

The marketing industry has never had greater access to data than it does today. However, data alone does not drive your marketing organization. Decisions do. And with all the recent hype regarding the potential of AI, a successful cross-channel campaign is propelled by a personalized, data-driven approach injected with machine [...]

SAS Customer Intelligence 360: Hybrid marketing and analytic's last mile [Part 1] was published on Customer Intelligence Blog.

8月 192019
 

In parts one and two of this blog series, we introduced the automation of AI (i.e., artificial intelligence) and natural language explanations applied to segmentation and marketing. Following this, we began marching down the path of practitioner-oriented examples, making the case for why we need it and where it applies. [...]

SAS Customer Intelligence 360: Automated AI and segmentation [Part 3] was published on Customer Intelligence Blog.

8月 122019
 

In part one of this blog series, we introduced the automation of AI (i.e., artificial intelligence) as a multifaceted and evolving topic for marketing and segmentation. After a discussion on maximizing the potential of a brand's first-party data, a machine learning method incorporating natural language explanations was provided in the context [...]

SAS Customer Intelligence 360: Automated AI and segmentation [Part 2] was published on Customer Intelligence Blog.

8月 052019
 

Marketers and brands have used segmentation as a technique to deliver customer personalization for communications, content, products, and services since the introduction of  customer relationship management (i.e., CRM) and database marketing. Within the context of segmentation, there are a variety of applications, ranging from consumer demographics, psychographics, geography, digital behavioral [...]

SAS Customer Intelligence 360: Automated AI and segmentation [Part 1] was published on Customer Intelligence Blog.

3月 282019
 

Over the past couple of years, I've written about a variety of use cases and value props regarding SAS® Customer Intelligence 360. As powerful as words and images can be, let's transition to the ultimate show – the demo. In the forty minute video below, observe how SAS Customer Intelligence [...]

SAS Customer Intelligence 360 Meets SAS Viya: Show me the demo was published on Customer Intelligence Blog.

4月 272018
 

Analyzing ticket sales and customer data for large sports and entertainment events is a complex endeavor. But SAS Visual Analytics makes it easy, with location analytics, customer segmentation, predictive artificial intelligence (AI) capabilities – and more. This blog post covers a brief overview of these features by using a fictitious event company [...]

Analyze ticket sales using location analytics and customer segmentation in SAS Visual Analytics was published on SAS Voices by Falko Schulz

1月 112017
 

One of the most powerful sales tools is often something that you can’t foresee or control. Even though customers read papers, visit websites and talk with a salesperson, another factor can make all the difference – a referral from a friend or coworker.

Think about the way that sites like Google, Yelp and others have changed the way consumers make everyday decisions, such asadvocacy choosing restaurants. You can go to the restaurant nearest you or one you’ve visited before. Or, you can try something new by looking at your smartphone to see which dining spot has the highest ratings or the best reviews. Why? People show a preference for the personal experience of those in their networks.

For business-to-business software companies like SAS, the impact of customer advocacy is critical. These influencers can set the tone and provide a consistent positive influence throughout the customer journey. Unfortunately, this type of advocacy is tough to measure and hard to predict.

The challenge: Acquisition and retention

Although a customer may be a single record in your database, she doesn’t exist in a vacuum. Each contact has a connection to others within her business or the industry. Understanding and fostering good relationships can have a huge effect on your retention and loyalty efforts.

During our effort to map a modern customer journey, the SAS marketing team focused on different phases of this cycle. The customer journey contained these phases:

  • Acquisition – which includes need, research, decide and buy.
  • Retention – which includes adopt, use and recommend.

On the retention side, the team knew from anecdotal evidence that some SAS customers were advocates of the technology and for the company overall. In fact, several SAS regional offices and divisions had data confirming the idea that finding and rewarding high-value customers led to big returns. What was lacking was an overarching program for getting customers to advocate for SAS technology.

For a larger effort, the team assessed the customer behavior data, examining those who attended events, provided feedback on surveys, sent ideas to R&D, and generally stayed engaged with the company. From a revenue standpoint, those people were often the ones advocating for the use of new SAS technologies or the expansion of existing deployments.

What was less understood was the reach of these influencers and how their activities affected others. With that information, SAS could identify more advocates and nurture that behavior.

The approach: Identify advocates by scoring BFF behaviors

The SAS marketing team members started by digging into the data that they had on customers. They first identified a segment of the top accounts that contained more than 20,000 individual contacts and the team began to examine the behaviors exhibited by that group including:

  • Live event attendance.
  • Website traffic.
  • Technical support queries.
  • Customer satisfaction survey data.
  • Customer reference activity.
  • Webinar attendance.
  • White paper downloads.

This information provided a better understanding of the range of activities that customers undertake. However, simply cataloging the behaviors wasn’t enough. The team applied a scoring model for different types of interactions. This allowed the team to weight certain activities, helping to further identify which customers were the best advocates—“BFFs” (best friends forever) as the marketing team began to call them.

The results: Advocacy campaigns that matter

SAS marketing used the information to create a model that is the foundation for customer-focused data exploration. The initial effort helped shed light on how influential advocates can shape retention and additional sales. As a result, sales and marketing worked together to highlight BFFs within key accounts in an ongoing effort to foster better relationships with those key individuals.

Initiatives to locate and encourage advocates used the model to identify the likely candidates within customer organizations. The team then designed campaigns and outreach efforts to give these advocates the tools to foster and expand their influence.

The marketing team now focuses on advocacy campaigns that target potential BFFs. The goal is to build more SAS advocacy during the recommend phase of the customer journey.

Acquisition and retention campaigns begin by doing advanced segmentation in SAS Marketing Automation. Campaign workflows are created that are backed by analytics, ensuring that communications to customers are appropriate and relevant. Through the collection of both contact and response history data, attribution can be performed in SAS Visual Analytics that allows marketers to see correlations and cross-promotion opportunities.

Interested in learning how to leverage SAS Marketing Automation techniques for advanced segmentation? Explore our SAS Marketing Automation: Designing and Executing Outbound Marketing Campaigns and Customer Segmentation Using SAS Enterprise Miner course offerings.

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Editor’s note: This post is part of a series excerpted from Adele Sweetwood’s book, The Analytical Marketer: How to Transform Your Marketing Organization. Each post is a real-world case study of how to improve your customers’ experience and optimize your marketing campaigns.

tags: Adele Sweetwood, customer advocacy, customer analytics, customer experience, customer journey, marketing automation, sas enterprise miner, sas marketing automation, segmentation, The Analytical Marketer

Customer advocates: Finding your customers’ BFFs was published on Customer Intelligence.