Matching Quality Applicants with Quality Jobs
Monster Canada (www.Monster.ca) is Canada's leading career management portal. To drive growth and provide outstanding service to employers and job seekers alike, it turned to SAS Customer Intelligence and SAS Analytics. As a result, the company has increased its sales productivity, marketing efficiency and customer retention rate by double digits.
Monster Canada – a bilingual, user-friendly online resource that is revolutionizing job seeking and recruitment – is headquartered in Montreal. It is part of Monster Worldwide Inc. (NASDAQ: MNST), the parent company of the leading global online career and recruitment resource. Monster Canada receives 3 million unique visitors a month, posts more than 2.5 million résumés and averages 35,000 Canadian job postings.
Monster Canada sells a variety of products and services to companies looking for employees – from basic access to posted job openings to advanced screening, online résumé-mining services and career site hosting. The company wanted to understand its clients better so it could offer the right mix of services, and it needed a better way to extract and organize its customer data, run its performance dashboards efficiently, analyze and segment its customers and job seekers, and provide the best results to its clients.
Monster Canada's first challenge was to extract information from its data store, which covers 36 countries – 3 terabytes of data. "It was very cumbersome,'' says Jean-Paul Isson, Senior Director of Global Business Intelligence and Predictive Analytics. Records from Canada alone total 50 million, and Isson wanted to bring in outside data from sources like Dun & Bradstreet and Statistics Canada. Before turning to SAS, Isson used an extraction tool and organized information in Excel files. The process was time-consuming, and his team couldn't do certain things, like analyze job postings. It was nearly impossible to incorporate outside data. The reports the team could generate – involving 4 million records – took one to two days to complete. With SAS, it now takes two or three hours.
Not only can Monster Canada do its simple reports more quickly, but it can also analyze data in ways that weren't possible before using SAS. Isson's team can now develop recency, frequency and monetary (RFM) segmentation to profile its customer base and build predictive models to score new prospects based on their propensity to buy certain kinds of services.
Using RFM and Web mining to help customers
"By applying the RFM segmentation to Monster Canada's customer base, we understand who our customers are and what they are doing, what they will do, and how we can help them get the best results with Monster," Isson says. That ability has enhanced Monster Canada's cross-selling and up-selling strategies, which increased marketing efficiency by 40 percent in one year. "We make sure every action our marketing and sales people take will be data driven and profitable,'' Isson says.
With SAS, Monster Canada has a complete picture of its customer. It can clearly identify its most profitable customers and products, thus enabling the company to use its resources more effectively to serve customer needs, proactively retain higher-value customers and sell Monster Canada's higher-margin products. "Our Web mining has enabled us to provide the best services and features to our clients and job seekers."
With SAS, Isson now performs advanced Web mining and analyzes job posting performance in ways that can help companies improve the quantity and quality of applicants they receive. For instance, Isson's team can compare every posting for a marketing analyst in Montreal and show customers how their posting compares to the average similar posting in terms of the number of viewers and the number of submitted résumés. If the company's posting is below average, Monster Canada suggests best practices to enhance it. "This is something we didn't have before, and it brings value to our customers because we are constantly helping them to get their expected results,'' Isson says. These types of services helped Monster Canada increase its customer retention rate by 15 percent and reinforce its thought leadership in the Industry.
Improving sales team efficiency
The company also uses SAS Enterprise Miner™ to improve the efficiency of its sales team. Isson recently analyzed internal and external data and developed a powerful business intelligence tool to score the 1.4 million Canadian companies in the Dun & Bradstreet database and rank those not yet using Monster Canada on the likelihood they would purchase services.
The BI scoring model helped divide prospect companies into three segments (high, medium and low) based on their potential value and propensity to buy. Isson's team took it one step further by developing an advanced calibration model to optimize Monster Canada's sales coverage. For the first time, the company could put together balanced prospect lists for new sales representatives. A group of sales reps was hired, and each rep was given the same mix of high, medium and low probability clients to contact. Monster Canada quickly figured out which new salespeople were the most successful and started to shift more important clients their way, further increasing success. As a result, sales productivity increased 40 percent.
"With SAS, we're able to address the four core objectives of the company," Isson says. "We know our customers better. We can show them that we can be advisors, which builds strong relationships. The customers are satisfied, which increases retention, and by segmenting our clients we can sell to the highest value niches. With the intelligence we add to our data, Monster Canada is a trusted advisor to the vast majority of clients iin the recruitment industry. As a result, we're seeing tremendous results.''
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.
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Senior Director, Global BI, Predictive Analytics
Monster Canada needed to extract and organize its data to enhance its customer and market knowledge and increase customer retention, market share and profitability through cross-selling and up-selling capabilities.
SAS provides customer intelligence and analytics capabilities that enable Monster Canada to segment customers and analyze marketing efficiency and sales force productivity.
During its first year of using SAS, Monster Canada increased customer retention by 15 percent, sales force productivity by 40 percent and marketing efficiency by 40 percent.
“By using SAS, we make sure every action our marketing and sales people take is data driven and profitable.”
Senior Director, Global BI, Predictive Analytics