Avoid overselling by finding the optimal telemarketing contact frequency.
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A business associate of mine recently inquired whether I had any information regarding industry standards for telemarketing contact frequencies. My colleague was also looking for any benchmark information that suggested how many times on average one needs to present an offer before the customer accepts it. Last, I was asked if I had any information on how much time should elapse between offer presentations. I must confess, I wasn't quite sure how to answer these questions and didn't have my crystal ball readily accessible.
Some sales experts have claimed that it takes up to seven or more ad exposures before prospective customers actually make a purchase. Several direct marketing issues have always been challenging: the identification of products or sequence of products to offer; the timing and frequency of contacts; and the investment threshold that stimulates a purchase. Unfortunately, the answers to these questions are always a big "it depends."
The factors that come into play include the nature of the product offer, the price point, the scripting, the quality of the interaction, and the contact sensitivity of the individual.
For direct marketers to address these questions, they need to conduct a customer-focused contact study measuring the effects of different contact patterns on cumulative sales and profitability.
Identifying the sensitivity of individual customers to repeated contacts is becoming increasingly important in implementing successful CRM initiatives for an organization. But the actual sensitivity levels to repeated contacts often will vary from person to person. Direct marketers have shied away from asking customers how often they would like to be solicited simply because they are afraid of what they may hear. These marketers fear that their customers may wish to limit any type of contact altogether.
To complicate matters, in a product-focused organization several independent product managers may separately be contacting the same customers every successive month regardless of what contact thresholds exist. This pattern may be the result of an attempt to implement several fixed interval, same-product contact strategies. For example, each specific product offering may be scheduled for every six months. But because several products are being offered at different six-month intervals, the net effect is monthly customer contact.
Contributing to the possibility of exceeding customer contact thresholds is the fact that there may not be business rules established limiting the number of times a customer may receive a direct mail solicitation preceding or following a telemarketing contact. This situation can easily result in the over-solicitation of an organization's best customers, and lead to the potential alienation of a profitable group, thereby negatively affecting future sales and incremental revenue.
Additional analysis of an organization's previous promotional and contact history--and customers' attitudes toward it--would be warranted to determine if alienation is indeed occurring. One approach is to design and develop a customer-focused contact study that would determine the optimal telemarketing contact frequency by measuring the effects of different contact patterns on cumulative sales and profitability.
Define testing environment
The initial development of a customer-focused contact study involves setting up an experimental design structure that tests alternative frequencies and intervals of contacts over a specified period of time within well-defined groups of like customers.
These customers should be split into multiple cells, or segments, including a control group that would not receive any contact throughout the testing period. The control group, as well as the various customer cells, may be exposed to multiple forms of a company's advertising, so it is imperative that the timing and duration of the study be carefully considered in conjunction with media plans to minimize this type of exposure.
The customer cells themselves should be defined based on a combination of factors, including the following:
Purchase history (RFM, or recency, frequency, and monetary)
Capturing purchase history allows us to examine how recently customers have purchased (recency), how often they purchase (frequency), and how much customers have spent (monetary). Using RFM analysis customers can be assigned a rank between one and five (with five being highest) for each RFM component. These scores can then be appended to the database to determine which customers are most likely to respond to an offer.
Although RFM analysis is a useful tool, it does have certain limitations. A common mistake marketers make is to oversolicit customers with the highest scores and ignore customers with lower scores. The low-scoring customers should not be neglected; they should be cultivated with the objective of migrating them toward a higher RFM ranking.
Product usage patterns
Capturing product life cycle and usage patterns is helpful in determining the timing of offers and achieving a certain degree of relevance when presenting an offer to the customer. Depending on the industry there may be seasonal patterns or time frames to consider when attempting to upsell or cross-sell additional products and services to customers.
Response or nonresponse to prior promotions
Knowing customers' promotional histories and their corresponding responses to each offer are key to developing accurate response models that can be used to predict future behavior patterns. Offer history and response information are often the most predictive variables for determining which customers or prospects are most likely to respond to future telemarketing programs.
Ideally customer-level promotion and response history should include a detailed description of each of the offers delivered, including the date of the promotion, the channel used, and the corresponding disposition.
Knowing the channel preferences of your customer base is key to developing and optimizing your internal sales and delivery systems. Customers will implicitly or explicitly reveal their channel preferences through their actual behavior and purchase patterns.
Channel preferences can also be determined through direct communications with your customers through research surveys, Web registration, call center interaction, and point-of-sale.
Determining customer contact preferences should not be limited to an evaluation of telemarketing. It should include testing multiple channels. For example, testing which sequence of e-mail, direct mail, and telemarketing works best and determining the cost of delivering communications through a particular channel or series of channels.
It may also be beneficial to analyze past frequency of contacts across
multiple channels in relationship to customers' "Do not solicit" requests.
Self-reported and third-party demographic, lifestyle, census data
Third-party demographic, lifestyle, and census data can be purchased from a number of reliable vendors and would augment the gaps in most data routinely collected from customers. These additional data provide the means necessary for defining target audiences and developing customer profiles.
Behavioral and other qualitative information captured from customer research and surveys
Attitudinal and behavioral data can provide additional knowledge and insight about what actually motivates a particular customer to make a purchase. Organizations can use qualitative information captured from customer research to position products and services according to customers' preferences and to boost overall response to specific marketing programs.
It is important that the testing environment be set up to capture, measure, and track the impact of your contact strategies accurately on each customer segment. Total cost of contacts during the time horizon should be measured as well as incremental sales for each segment or cell. Developing a process for quantifying return on investment for various contact scenarios under a semicontrolled environment will assist in optimizing the results of future promotions.
Once the results of the customer-focused contact strategy are compiled, narrative "résumés" can be created for each segment, which will help organizations determine what type of sales approach should be taken with each of their customers in the future.
Capturing and understanding the behavior and characteristics of one's customer base provides a solid foundation of business intelligence and is key to implementing any type of successful CRM initiative.
Keep it Simple
Although the testing environment could include any number of possible contact combinations, only a limited set of reasonable tactics should be explored. Given the multitude of possible contact permutations, contact strategies can quickly become extremely complex and unmanageable. Adding to the complexity is the fact that a customer's contact preferences may change over time and that certain customers may migrate between RFM segments. Therefore, it is imperative that the customer-focused contact study be kept within a manageable size and time frame.
Successful enterprises develop and implement customer contact strategies based on their customers' behavior and individual contact frequency preferences. These organizations have mastered the challenge of managing a contact strategy in spite of a multitude of touch-points and contact channels (inbound and outbound). Collecting extensive information and customer data at every point of contact may prove impractical, but with a disciplined approach and a methodical contact strategy based on findings from a customer-focused contact study, optimal results for future CRM initiatives can and will be achieved.
Proactive contact is the new customer service imperative.