Click here to
|Lead scoring: A qualitative approach to increasing sales efficiency|
by Christopher Hornbeck
|The sales and marketing apparatuses of the vacation ownership industry are, by and large, models of inefficiency, historically relying upon broad-based marketing techniques and using internally agreed-upon sets of qualifications to determine customer suitability. Multitudes of people who may or may not fit said qualifications, which are usually based solely on age, income, and marital status, are led through an elaborate set of sales funnels and marketing processes with the hope that a significant number of “qualified” prospects are retained long enough to reach a sales table. This cumbersome process continually erodes the potential customer base, step-by-step, until a few precious purchasers remain.|
In today’s economic climate, developers can scarcely afford to expend precious marketing dollars to generate huge numbers of prospects in the hopes of gaining sales velocity by brute force or sheer volume; neither is it any longer a viable option to turn away potential buyers because they may not fit into antiquated notions of “traditional qualifications”.
To meet these challenges, many organizations are turning to intensive demographic analysis and business intelligence methodologies to create cutting-edge lead scoring systems, which, if correctly implemented, can give marketers a much clearer picture of who their buyers actually are and the actions they must take to effectively market to those segments.
Technical methods, such as demographic and psychographic data appension, credit scoring, and the application of data mining algorithms to past and current customer databases, can help to produce “ideal buyer” profiles, which can be utilized to communicate with and market to prospects that best fit the organization’s product offerings in terms of willingness and ability to purchase. Grades or scores based on relative similarity to these “ideal” profiles, which can be adjusted over time to incorporate new data, are assigned to individual leads or customers so they can be effectively prioritized.
Lead scoring models are based on explicit and implicit data learned about the potential customer through a number of different means. Examples of explicit data (which might, for instance, be gleaned either through a pre-arrival survey card or through modern data appension techniques) include common demographic metrics such as age, household income, and geographic location, but also more telling sales readiness indicators like credit score, home value, and loan-to-asset ratio.
Implicit data, on the other hand, includes measurements of things like customer behavior, lifestyle choices, and product loyalty. This kind of data, which can be collected at the point of initial lead generation, in pre-arrival screening, or through psychographic data purchase, can shed light on important variables like whether the potential customer enjoyed their pre-tour accommodations, what types of leisure activities they enjoy, or the number of times they have toured in the past.
Because explicit data can sometimes be skewed or partially incorrect due to user input, a comprehensive demographic scoring system incorporates both explicit and implicit data to rank potential leads in order of both their willingness and their ability to buy the product.
Lead scoring implementation can be as simple as pulling a credit score on every tour, or as complex as the use of algorithmic data modeling, which instantaneously produces scores by combining demographic metrics and behavioral data and comparing them against ideal buyer profiles produced through trend analysis.
Regardless of the method used, the general purpose remains the same: to segment and prioritize lead and tour pipelines so that sales and marketing assets can be deployed most efficiently and customers are offered the right products to fit their needs and budget.
Scoring systems can be incorporated into the marketing process at almost every step. Lead generation efforts can be targeted to geographic areas that produce the highest scores, call queues in outbound call centers can identify and serve up the highest scoring leads first, and Internet advertising can be placed to fit the indicated lifestyle and demographic categories of potential clients. This type of prioritization helps to ensure that groups of likely eventual purchasers receive the marketing budget allocation and customer service attention they deserve.
A common mistake is to use a demographic scoring system to filter, not to prioritize, a customer or lead database. Just because someone doesn’t rate an “A” or “B” does not mean they are not still a potential customer. Lead scoring simply identifies the most likely buyers based on the criteria set forth and past trends, but great success can also be had by tailoring specific sales procedures to “lower scoring” tours, either by changing sales pitches or offering different products. A scoring system should never be used to “throw away” leads and tours that have already been purchased.
On the sales floor, scoring systems can be used to effectively manage risk across sales representatives with varying ability levels. Assigning tours with the highest likelihood of purchase to reps with less experience, while at the same time allowing tours that receive a relatively lower score from an Interest-based standpoint (but are still able to purchase) to flow to more experienced salespeople, can produce significant increases in overall sales efficiency.
By employing lead scoring methodology, vacation and travel products can be tiered to better fit customer budget and need, presenting more expensive packages to the people who can best afford them and desire them, and promoting more modest, lower-cost options for those who may have a more limited income or exhibit less need.
Implementing a demographic scoring model, and committing to the subsequent sales and marketing opportunities it creates, can produce leads and tours that are more cost-effective, higher-converting, and (ideally) of a greater overall volume due to lack of restrictive traditional qualifications. Added benefits include the creation of stronger bonds between sometimes disparate sales and marketing teams and the promotion of increased accountability across the entire organization.