Omnichannel with ML Blockchain

Despite the prevalence of new advertising and promotional channels and significant investments in data and technology, marketers are still struggling to generate and to prove sales results in an increasingly omnichannel world.

—Eric Solomon, Senior Vice President, Nielsen

Omnichannel marketing is heralded as the future of retail, but remains mired with obstacles. In a recent paper, we investigate three challenges in realizing the full potential of omnichannel marketing: (1) data access and integration, (2) marketing attribution, and (3) consumer privacy protection. Our main message is that advances in machine learning and blockchain offer some promising solutions.

Omnichannel is the synergetic management of the numerous available channels and customer touchpoints, in such a way that the customer experience across channels and the performance over channels is optimized. Ideally, customers interact seamlessly with the company across channels both internal and external to the company, and the company has full information on all customer touchpoints to provide a single unified experience across channels. In reality, companies struggle with 3 key challenges:

  1. Data Challenges: Tofully realize the potential of omnichannel marketing, companies need information on all their interactions with each customer during the different stages of the customer journey. We include consideration of the communications between the firm and its customers, activities where the customers interact with the company (or its partners) while gathering information, making a purchase, receiving the product, making a return, and receiving postpurchase service. Such data might not be readily available or easily usable.
  2. Marketing Attribution Challenges: For optimizing the customer experience across all channels, companies need to know the impact of various touchpoints on behavior and measure the return on investment of its marketing spend. In our opening quote from Eric Solomon, this is captured as “prove sales results.” Such analysis may be challenging when the effect of a touchpoint can transcend multiple stages in the purchase funnel, when several occur concurrently, or when consumers go back and forth between different stages in their path-to-purchase journey.
  3. Customer Privacy Challenges: The promise of omnichannel marketing relies on using data on all the interactions between the company and its customers. However, this can come at the cost of infringing on customer privacy. Therefore, an important challenge for a company is determining how to embrace an omnichannel strategy while respecting consumers’ privacy.

In the paper, we elaborate on how blockchain and machine learning developments can overcome these challenges to help companies reach the full potential of omnichannel marketing:

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