In our March installment we began to peel back the onion on Multi-Channel 2.0 (MC2), exposing some of the critical process elements and their extraordinary value throughout the sample management continuum. In this final installment, we review critical data elements involved in best-of-breed solutions.


Starting at the end may sound odd, but you probably do it often. The “end” in this case is a “goal.” Every program starts with establishing the customer’s goals—corporate, brand, project, and provider segments. Other critical factors include understanding the brand’s lifecycle status and project timeframes. Budget tracking, of course, is always a key element— often broken down strategically by provider segment, marketing channel, and action/request type.

MC2 by nature is highly dynamic, enabling choice, identifying preferences, and shifting emphasis to achieve maximum efficiency and customer satisfaction. Creating efficiency (rather than chaos) in such an environment requires full transparency and real-time visibility to data. Iterative reporting is fed through the specialized MC2 data structure to produce metrics that quickly identify trends critical to tuning performance of the multi-channel engine.


It is, indeed, “all about the data.” The data structure is the foundation, and the bedrock beneath is an identification system incorporating state-of-the art matching algorithms to insure the unique identification of all providers. MC2 measures the impact of events at the provider level, so a detailed, upfront provider-discovery process is critical. All provider sources and corresponding identifiers must be determined and a unique code assigned for each data source. Provider types and demographics, including update and append requirements, need to be recognized. Rep/territory designations at the provider level are also important, since these relationships can often be a major contributor to multichannel reporting/analysis and sales representative integration.

Many pharma companies group their provider targets into five categories: key opinion leaders (KOL), early adopters (EA), and high, medium, and low writers. While this is generally consistent across our industry, it is also important to define any other segmentation that may be unique to a particular company, brand, or individual campaign. Identifying the target provider groups is essential: messaging and delivery strategies often align at the target group level. KOLs and EAs often have unique messaging and delivery strategies. High, medium, and low writers often have common messaging while delivery strategies may vary based upon cost, timing, or objective. Every provider has a customer-established weighting, often referred to as “Provider Value.” The Provider Value is usually derived from prescription- level data and is assigned at a provider/brand level. By establishing clear timeframes and activities to incorporate into reporting metrics, one can produce a post-Provider Value correlated to each sampling event or combination of events.

Personal and non-personal promotional activities are applied, either independently or in combination, to produce “outbound” events. Correlated response structures capture activities and responses for each resulting “inbound” event (or response). Every event and every response is captured by time, date, channel, brand, provider, etc., and should include cost and the rep/territory designation data.


Reports and real-time data views are designed to measure the effectiveness of MC2 event activities, both immediately and over time, providing insights into:

  • Provider/event level responses, including the importance of null or no response,
  • Impact of events by provider/brand, along with associated planned-vs.-actual cost,
  • Provider/event/response at rep/territory level, with or without associated personal activity, and
  • Preference-level data by brand, event, and provider, with stated vs. demonstrated preference, if available.

While specific program objectives may vary, such metrics must be defined and aligned to the customer’s goals in order to provide such subsequent deliverables as:

  • Event ranking by provider over time,
  • Demographic patterns and trends (including cost per target and/or cost per demographic),
  • Predictive analysis of events by provider/brand, and
  • Recommended adjustments to segment(s) or channel strategies and tactics.

Many other key data views are required to provide the highest degrees of success throughout and across each multi-channel program. It is important to note, though, that over-analyzing or micro-managing are easy traps to fall into as depth and visibility of data increase. Careful data-structure planning, coupled with the right views and tools, will provide a window to the soul of your provider’s preferences. And understanding these preferences is the key to efficiency goal of Multi-Channel 2.0.

  • Michael Laferrera

    Mike Laferrera is President of J. Knipper and Company, Inc., a leading pharmaceutical marketing and fulfillment company specializing in complete sample management solutions and dedicated to the pharmaceutical and life science industries. With a top track record for developing domestic and global sales and marketing solutions over his 20 years in Pharma, Mike leads all of Knipper


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