Customer service leaders across North America are gearing up for retail’s busiest season. Traditionally, much of this preparedness has been centered on staffing up to handle peak volume, strategizing to meet KPIs, hardening websites and IT infrastructure, and optimizing inventory and delivery. Fortunately, as a result of the growth of artificial intelligence, automation, and predictive analytics, tides are turning in retail, and this could be one of the final seasons in which we have to rely on tried and true ramp-up techniques.

Here are some pointers to help you prepare for both the present and the future of retail customer experience.

Reducing contact center turmoil during the busiest season

While the holidays are not the best time to test out something completely new, implementing little changes now can improve peak manageability and prepare your company for future automation projects.

Simple modifications might boost your automated business case. In the front office, for example, many customer service representatives, with the assistance of IT, have already automated (e.g., utilizing IVR, scripts, email reminders and alerts) some client interactions such as product and store locators, gift card balances, and password reset. In addition to traditional automation strategies, implementing an SMS/text notification strategy for order status updates, shipping alerts, and return confirmations is entirely feasible in the weeks leading up to Black Friday, reducing the need for additional agents and contacts in their centers.

Automation, in addition to decreasing headcount, can increase revenue. In one successful e-commerce business, a well-known producer and online retailer of camping equipment increased conversion rates by 40% after developing and implementing an abandoned shopping cart approach. When a buyer withdrew an item from his/her online shopping cart, an immediate 10% discount offer appeared. If the customer accepted the 10% discount, a live chat agent arrived and completed the deal.

Even for merchants who are hesitant to automate customer-facing procedures, there are opportunities to apply robotic process automation (RPA) for back office processes such as agent screen transitions and lookups in order to respond to incoming requests more quickly.

Manage social media volume spikes by employing AI

One of the most difficult aspects of social media management is dealing with an increasing volume of postings while having limited resources. Engaging with actionable posts and screening out non-actionable posts takes time. To address this issue, marketers can create an AI model that extracts spam, news items, retweets, international postings, and other non-actionable information, saving agents important time reading posts that do not require a response. In addition, AI can be utilized to help prioritize posts in terms of importance. For example, those in which consumers are in-store shopping and require quick assistance in locating an item would be prioritized over those in which customers ask standard customer service questions, such as store hours.

Utilize predictive analytics to capitalize on clients’ next move

Customers can now easily ‘engage’ and ‘purchase’ through channels such as mobile, social media, and e-commerce. At the same time, customers have begun to expect much more from companies, such as consistent experiences across channels that represent their history, preferences, and interests. Customer service leaders want access to a single customer data platform that can give them with data-driven insights to better understand each customer’s profile, journey, and history across channels. Then, customer service leaders should use a predictive analytical model to become proactive in customer engagement strategies such as predicting the next step in the customer journey, understanding your high-value customers and their purchasing behavior, predicting customer churn, and recommending cross-sell offers that customers are likely to accept.

How to Prepare and Execute

CX automation, analytics, and AI are best implemented in stages. It can take six to twelve months to design, execute, and optimize the model and strike the proper balance between bots (machines) and brains (people). Taking the jump usually involves:

• Mapping the customer (and agent) journey both in the front and back office.
• Hiring a data analyst to review previous contact driver reports.
• Objectively identifying the top ten reasons clients contact you.
• Determining which of the ten contact types could be fully automated, partially automated, or prohibited.
• Mapping the customer and agent journeys for each contact type.
• Seeking a partner with AI, analytics, and automation capabilities.

Forward-thinking businesses are already leveraging a combination of bots and brains to provide next-generation customer experiences and optimize operations. Even though the Christmas season is quickly approaching, now is an excellent time to start planning for next year’s continuous improvement projects in order to remain competitive.