The retail world is undergoing a disruption of almost unimaginable scale. Rapid technology changes, new sales channels, empowered consumers, rising costs of sale, increased speed to market, not to mention a global pandemic, are all materially and permanently transforming the ways that consumers shop and their expectations while doing so. Brands are finding that their need to connect with customers in ways that are more personalized, relevant, and ultimately, profitable necessarily leads them towards four areas of technology:
ADVANCED, UNIFIED ANALYTICS
OMNI-CHANNEL CUSTOMER ENGAGEMENT
PERSONALISATION & CONTEXT
SCALABLE & INTELLIGENT CUSTOMER SUPPORT
Better Customer Intelligence Through Advanced, Unified Analytics
We help clients unleash advanced analytics on rich data to turn customer insights into retail excellence. Direct customer relationships are a privilege, but they also generate massive amounts of data. This wealth of information holds the potential to drive real frontline differentiation, if retailers have the right tools and approaches to make the most of this unique asset.
Our analytical experts have the knowledge and the practical experience to work with disparate data sources, generate relevant insights, and derive a rich fact base to support business decisions for all key retail business processes.
Insights-driven retail merchandizing: Based on transaction or loyalty data, we conduct targeted data mining to help retailers make informed decisions about pricing, promotions, and assortment management.
Insights-driven retail marketing: To make marketing investments where they really matter, we help clients apply advanced analytics to customer lifecycle management and marketing mix modeling.
Insights-driven retail operations: We help retailers pinpoint improvement opportunities across the entire supply chain, from sourcing and purchasing to in-store availability management.
Using Chatbots to Lead an Omnichannel Strategy
Customers want an integrated shopping experience. They expect you to meet their needs and demands even when they use different channels to communicate. You might understand the value of being present in multiple channels but not have the resources to be able to properly support your customers in each one of these, and this is where an omnichannel chatbot comes into play.
An omnichannel chatbot can be successfully implemented in multiple channels like your website, Facebook Messenger, WhatsApp, Alexa, and wherever users interact but can still be managed from a single platform. Some chatbots even offer integrations with voice and live channels — and in multiple languages — so that clients can call Customer Service or contact a human agent at any time during the conversation.
But working seamlessly across all channels is just the first step. Aside from that, omnichannel customer service also implies considering customers as individuals, analyzing their records, understanding how they interact and knowing their interests and preferences. Once again, chatbots come in handy since they are made to customize each user’s experience.
Then, once the data is collected, chatbots engage in personalized conversations by understanding each customer’s intention behind their question, they access real-time customer data, and adapt the messages to each individual’s situation.
Then, once the data is collected, chatbots engage in personalized conversations by understanding each customer’s intention behind their question, they access real-time customer data, and adapt the messages to each individual’s situation.
Retail sales from chatbot-based interactions are forecast to almost double every year to $112 billion by 2023 from $7.3 billion this year [and] chatbot interactions also will surge from 2.6 billion to 22 billion over the same period.
Enabling the Next Level of Personalisation
Numerous studies prove that customers increasingly prefer a shopping experience that’s easy and fast and that helps them make purchase decisions. Best-in-class retailers are using personalisation to make the shopping experience as easy, fast, intuitive, and seamless as possible across touch points. In most cases, success requires building personalisation capabilities, which is critical for maximizing the value of the vast amount of data that is available on individual customers’ preferences. But success doesn’t necessarily mean developing a unique experience for every customer at every step of the way—an undertaking that can be very costly. Rather, the goal for leaders is to use technology to personalize critical touch points in a way that best drives value for the customer and retailer. The size of the personalisation opportunity varies depending on a retailer’s current personalisation capabilities. Even if a retailer has significant capabilities, however, its growth potential can still be substantial. All retailers—even leaders—should make advancing to the next personalisation maturity level a strategic priority.
When the shopping experience was highly personalized, customers indicated that they were 110% more likely to add additional items to their baskets and 40% more likely to spend more than they had planned.
Although customers are not inclined to consider personalisation as an end in itself, customer surveys suggests that personalisation done well can result in significant benefits to the retailer. For example, when the shopping experience was highly personalized, customers indicated that they were 110% more likely to add additional items to their baskets and 40% more likely to spend more than they had planned. Moreover, when asked to rate a particular retailer, customers who experienced a high level of personalisation provided net promoter scores that were 20% higher than those of customers who experienced a low level of personalisation. In short, personalisation is key to achieving what surveyed retailers said were their top business objectives: raising the rate at which they convert shoppers into customers and increasing the lifetime value of customers.
Conversational Ai is Revolutionizing the Face of Customer Service and Relationship Management
Automation of work in contact centers is not a new topic. IVRs have supported and simplified the work of telephone agents during the last decade, but are too “robotic” and rigid for most users. But a new range of chatbot and virtual assistant solutions based on Conversational Ai platforms provide the sophistication and flexibility necessary to deploy highly scalable support systems that offer natural written and/or verbal interaction with support systems.
Based on natural language processing (NLP) technology, these systems can range from simple canned responses to cutting-edge artificial intelligence (Ai) powering multilingual interactions. And seamless “human in the loop” technology allows the system to leverage human expertise when confronted with unusually challenging issues. Typical results are a 30% drop in support costs while increasing customer satisfaction by 40%.
Advanced Data Management: The Foundation of Retail Transformation
The merchant who best understands his or her customers has the greatest chances of success, and the starting place for these businesses is understanding the importance of data and having it all in one place — a single source of truth. A holistic view of the business makes it far easier to implement improvements and scale with the growth of the business.
This data is often scattered across multiple data sources within the business, data that must be desiloed, cleansed, and normalized. In addition, this first-party data can be supplemented by third-party customer data collected by external organisations that are not the original sources of the data. Examples of third-party data are demographics and information provider by vendors.
In the case of both first-party and third-party data, easy and rapid integration can be a huge challenge. SmarTek21’s Data Management and Strategy practice can help organisations ensure that their technologies, processes, and culture transform their data into an active business asset that helps drives their business forward.