The Case for Commercial Data The Time to Act is Now

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1 Today, we have access to a vast amount of customer data that can be used to power sales and marketing efforts. That may not be the case tomorrow. behind. Currently, regulations for customer data are looser than for consumer data, but that is changing. In the future collecting customer data will be more difficult and costly than it is today. Prompted by privacy concerns, regulators in Europe and Canada have already taken significant measures to restrict the use of data. The United States isn t far Businesses that don t act soon to build a data strategy will be left at a competitive disadvantage. The Value of Commercial Data Commercial data is defined as customer, market, competitive and industry data. It is collected through customer interactions, industry reports, web sites, online forms, transactions, lists, and third party sources. Commercial data, like any other, is worthless unless it s used to develop actionable insights. insight into purchasing patterns and customer behaviors across touch points, allowing for targeted messaging that in turn can boost repeat sales and customer retention. It can improve effectiveness at the top and bottom of the sales funnel. The data can be used to improve the efficiency and effectiveness of customer acquisition and to provide Marketing Efficiencies Model customer behavior to launch campaigns with predictable results Sales Efficiencies Drive efficiencies in the sales cycle reduce the average sales cycle and increase the average deal size Leverage real-time and dynamic voice of customer data to improve segmentation and targeting Develop more focused, targeted marketing campaigns in the most cost effective manner Generate more effective, qualified leads Develop highly refined customer specific communication and value propositions A strong signal of the place of data in marketing is IBM s March 2014 announcement that it will invest $100 million and hire 1,000 staff for a marketing consulting group with a major focus on data analytics. In fact, companies large and small are taking important steps to turn their data into knowledge.

2 Basic Steps Targeted s, personalization of web site experiences and lead generation driven by marketing automation platforms can be relatively straightforward forays into leveraging data. Historical data, deep analysis and third party data can make them richer and even more effective but those often can be added later, and it s important to begin capturing and using data sooner rather than later. CASE STUDIES Cartelligent helps clients throughout California buy or lease any make or model new car. Its services include consulting, locating, negotiating, trade-ins, delivery, and after-market products. The company did little outbound marketing beyond a periodic newsletter. While it tracked when leases were ending for existing clients, the company had no automated process for reaching out to lease-holders. By syncing its CRM with a marketing automation platform and integrating lease data, Cartelligent was able to generate a lead automatically for each maturing lease and to the appropriate account executive for follow up. The company also began an automated campaign that sends a survey to every client after a car is delivered and s the results to account executives and their branch managers. If the client rates the experience as favorable, a second asks them to like Cartelligent on Facebook and write a review on Yelp. As a result of these efforts, Cartelligent s Lease Portfolio Program revenue rose more than 171% in a year, and leads were up well over 50%. Thomas Cook Group is one of the largest travel services businesses, arranging flights, hotels and vacations for 23.6 million customers a year. Customers who booked through its Sears Travel and Thomas Cook retail stores were not being added to the company s central CRM database. Thomas Cook linked the data via its marketing platform, giving it the ability to send targeted, personalized s based on customers previous purchases. Its agents could create follow-up campaigns incorporating customers names, along with destinations and vacation deals. As a result, open rates nearly doubled from an average 25%-35% to 50%-60%. Further, the company has captured even more data through this process. 1 Marketo Case Study 2 ExactTarget Case Study

3 Intermediate Steps Customer segmentation may involve more than just our own historical data and may take more time and effort than web-based lead generation and targeting projects. Consolidation and analysis can add great value to the more basic efforts. They also are likely to provide insights or raise questions that can lead to additional efficiencies, innovation and new opportunities. CASE STUDIES Based on insights gathered through a survey of 2,000 customers, GE Capital ANZ has been able to move beyond a one channel fits all approach to one that allows targeting customers based on online behaviors and interaction with financial products. As a result, the division hopes to create a better customer experience with personalized content, to better target profitable segments, to engage more with profitable customers, and to turn them into brand advocates. Staples B2B is the world s largest office product company with $25B in sales. To increase sales across multiple B2B channels, Staples wanted to identify new multichannel buyer prospects that would drive market share as well as increase customer lifetime value and loyalty through the delivery of greater buying convenience. To do this, the team tapped into multiple data sources to create a custom prospect model. The model improved targeting by identifying businesses that would most likely repurchase a specific product and then cross sell into businesses that had not purchased the product. Through inmarket campaigns, the model resulted in a 5x improvement over previous campaigns. The result was a 40% increase in customer acquisition response 3 Epsilon Case Study

4 Advanced Steps More detailed analytics and integration of third-party data, especially in real time, entails much greater coordination, systems and engineering than lead generation, targeting and segmentation efforts, although deeper and more automated can ultimately enhance those projects. The more data, the more complex the project, but third party data management platforms can reduce the amount of internal programming that is needed. CASE STUDIES Dell deployed sales data intelligence software across all major B2B operating divisions in order to drive sales productivity while ensuring seamless integration with existing CRM systems and sales processes. Millions of data points from internal and external sources were consolidated to generate insights for the sales team. Customer data were used to prioritize cross-sell leads, allow sales teams personalize customer messaging, and pinpoint the highest prospect customer. The result was a lift in revenue through intelligent account targeting and contextual sales conversation. VMware, the vendor of computer virtualization software, deployed a sales intelligence system to its field and inside sales reps for all major North American segments. The sales reps were able to identify and engage with the most valuable and most likely customer opportunities, pinpoint buying locations, anticipate sales opportunities, and engage customers in contextual and timely discussions. The result was a 7% increase in sales productivity one year. 4 Lattice Engines Case Study 5 Lattice Engines Case Study No Time like the Present Getting Started is Easy Turning big data into actionable intelligence may sound daunting, but even small steps can make a huge long-term difference like optimizing contact us forms and including an opt-in button there, or by ensuring that your privacy policy allows sharing data across GE businesses.

5 Breaking it down... As you contemplate next steps, it will help to understand current commercial data practices. There are three pillars that support an effective commercial data strategy: Data Capture In most cases, data comes from a wide range of disparate sources. As such, it s important to collect as much meaningful data as possible and ensure data hygiene principles are followed. This means that the most relevant commercial data are captured in a way that s easily accessible and usable. Data Consolidation Because commercial data is collected across a variety of channels, it is important to consolidate the data into one central repository. This helps prevent duplication of effort and data redundancy, and offers a central database to analyze. Data Analytics & Utilization Even with the proper data structure, it is possible to become data rich and information poor. Once consolidated, data need to be analyzed to develop actionable customer insights. Successful analysis yields addressable customer segments, behaviors, and needs, allowing commercial teams to develop predictive models. And building it up. There will be lots of ways to get to success, but let s look at a few short and long term strategies 1 Permissions - One way to circumvent future and current legislation is to focus on permissions. This is easy. Every interaction we have with a customer or prospect needs to be tracked into an or social relationship that will allow GE to track engagement. If GE has current relationship programs in place via and social channels, GE will have limited its downside.

6 2 Structure - Structural databases that enable modeling are an investment. The Software COE is certainly looking at this capacity and could have scale solutions, but there are other methods from Adobe, SFDC, and Marketo that offer fast starts. 3 Look Externally - Form partnerships now with other companies, especially businesses with broad potential customer bases and data relevant to our businesses. Companies like BlueKai, X+1 and Bizo can help GE identify, segment and re-target customers and prospects 4 People The customer journey has been forever impacted by digital tools. Given the number of portals, apps, web sites and other touch points we have with our customers, map the journeys and identify someone in your organization to be a Digital Customer Experience Lead with accountability to streamline the data and create a seamless experience. Leveraging commercial data will have a broad business impact, resulting in more effective marketing and efficiencies throughout the sales cycle. Starting the conversation is more important than ever. Delaying will result in missed opportunities as future regulations are likely to restrict the use of data. Once you ve made the commitment to begin the conversation about building a data strategy, there are two simple steps: Understand your goals: This is crucial. 1 What specific problem is your business 2 addressing with customer data? What questions do you hope to answer? What will define success? Contact the Digital Commercialization team to help facilitate the discussion. Contact the Digital Commercialization team to help facilitate the discussion. If we don t act now, we ll be left trying to play catch-up to those that did.