Typically, multi-channel refers to sales efforts across several platforms. Such as retail stores, website, call center, and search engine results all impacting the same customers. Optimization across all channels--without cannibalizing the performance of one channel in order to achieve higher sales in another--is crucial. “Multi-channel” can apply to many different industries and problem types--increasing performance of the goal by driving performance of each channel is attained through statistical design. Doctors, nurses, telephonic care, and pharmaceutical treatments all impact the same patient in a health system or CM/DM, for example. Most of today’s big questions are comprised of enough moving pieces that a multi-channel approach proves the strongest way to achieve sustainable, safe, and fast performance breakthrough.
Nobigroup has perfected the solution:
Sophisticated multi-channel problems require sophisticated solutions, made easy for users. By blending knowledge of client issues with statistical methodology, Nobigroup is able to solve this complex problem by finding the triggers and synergies among channels. By testing a large number of ideas aimed at innovation, cultivated by working within the organization, Nobigroup unlocks organizational energy and leaps with our clients to breakthrough-attaining solutions. Remarkably, the complex analyses and methods are extremely user friendly for our clients. Our strength is in achieving and unlocking clever, elegant solutions in an easily understandable way.
Statistical Design is the evolution beyond the industry-standard of slow, single-channel, 1-4 variant testing to allow evaluation of over a million combinations across channels. This system of analysis works with our clients' existing resources, and provides usable results in a fraction of the time compared to traditional methods.
How does statistical design in multi-channel sales applications deliver results?
The results of an actual variant test are shown below:
Variant #1: A tactic was found to have helped in one channel, but hurt in another.
Variant #2: A segmentation tactic was found to hurt though it appeared (and was assumed) from best available knowledge that it would improve results.
Variant #3: The tactic adjusted the frequency of a sales event for further sales. In this way sales are maximized by surgically precise policies interwoven across channels. In this case the immediate improvement was about 15% and long-term improvement hovered around 10% but additional applications of the method continued the upward curve.
Variant #4: This segmentation found synergies where simple changes worked well together and found the “sweet-spot” in consumer triggers, disagreeing with previous market research results.