Salesforce launches Einstein, is this relevant for Omni-channel Retail profitability?

06 Oct

Salesforce launches Einstein, is this relevant for Omni-channel Retail profitability?

Ivano Ortis IDC

Ivano Ortis
Associate Vice President, IDC Retail Insights & IDC Manufacturing Insights

Read full bio  @ivanoortis

Andrea Sangalli IDC

Andrea Sangalli
Associate Research Director, IDC Retail Insights

Read full bio  @andrewsangs

Giulio Raffaele
Senior Research Analyst, IDC Retail Insights

Read full bio  @GiulioIdc

On September 19th Salesforce has announced the launch of Salesforce Einstein, its proprietary AI suite dedicated to CRM. This follows a string of acquisitions for the company’s SalesforceIQ unit including RelateIQ in 2014, Tempo AI in 2015, and PredictionIO earlier 2016, to arrive at MetaMind (an image analytics and machine learning startup) in April 2016. As mentioned, the peculiar aspect of this platform is that it is native inside Salesforce systems, thus allowing to be used on CRM core products and to provide Cloud AI capabilities to LOB ranging from Sales to Marketing.

At the base there is the institution of a group focused on AI innovation research – composed by 175 data scientist – and on the background two years of work with $600 million investments. Having such a research group inside the organization is a key factor for the CRM company as, at the moment, R&D on AI is mainly delivered by AI native companies and implemented by end-users through an integration layer. In this context, Salesforce thus shows the path towards a growing number of vertical platform companies acquiring AI focused companies (startups and mature ones) and investing considerable amounts of resources in order to develop proprietary AI platforms that are adapted to their own products and solutions.

Now, will these evolutions in AI help deliver profitable Omni-channel performance and how?

For Retailers, the great value of such development is the possibility to adopt a ready to use platform that collects and manages all customer interaction data, applying AI algorithms (contextual and historical customer data) and providing exclusive customer experience with individually targeted real-time actions.

If we extend the concept of the human genome to the sphere of Omni-channel Retail Customer Experience, every single customer interaction that will be collected and analyzed can be considered as a building block of Customer Experience (CX) genome. Thus, we can imagine creating the CX genome including data such as browsing and shopping basket contents, cart and checkout behavior, delivery option preferences, interests, attitudes about brands, cookie IDs (eg. collected by a DMP platform) and such like. In turn, if we consider every component of the Omni-channel Retail ecosystem as a carrier of a specific genome, fundamental will be the integration between the customer genome and merchandise and product genome. As for symbiotic organisms, basing on AI analysis of customer data, retailers will have the opportunity to take effective and automated decisions about targeted assortment, content and pricing.

CX genome is the next frontier for Retail Industry: using cognitive computing capabilities you gain an understanding of how all the information, coming from a multitude of channels and devices, work together, driving deeper customer insight to establish context and deliver an exclusive customer experience in acceptable, convenient, manner for each individual customer.

Data fusion plays a key role to make exclusive customer experience a reality: through it Retailers are able to build the CX genome, having a consistent and holistic view of the customer that include historical customer data, contextual data (gathered in real-time) and third-party data. One of the most important innovations introduced by AI is the possibility to merge independent sets of data – structured and unstructured – that so far have always been very complex to interfuse and analyze. This innovative approach is changing the knowledge map from customer behavior to the characterization of its social context, potential needs and decision-making.

IDC Retail Insights envisions some short-term implementations of CRM AI inside Retail Industry, that companies should include in their digital transformation agenda: for example, by 2017, intelligent assistants will become a necessary solution for building real-time and context-aware omni-channel customer interactions, based on machine learning and big data capabilities. Further to customer facing application, thanks to intelligent agents, AI will enable a very relevant shift in the way each actor of a retail organization works. Could the involved actor be a merchant, a marketer, a planner or an operator, the increase of productivity will be the main result, coming along with improvements in KPIs such as accuracy in supplying, out-of-stock level reduction, customer conversion and retention rate.

IDC Retail Insights sees AI as one of the most relevant factors impacting the Omni-channel Retail ecosystem evolution, that has built itself on many different types of retail genomes interacting with CX genome.

If you’re interested in learning more about this topic or want to learn more about IDC Retail Insights, please contact Ivano Ortis, Andrea Sangalli or Giulio Raffaele.

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