In a nation of people known for their politeness, Canadian business owners have always been keen on customer service. More than ever, today's big data can help business owners deliver superior customer service and meet customers' needs—often before they even realize a need exists. Thanks to big data and its use for predictive analytics, machine learning and artificial intelligence (AI), the landscape of Canadian marketing and customer service is changing—and driving business owners toward new frontiers.

According to the American Express report SME Pulse 2019, 19% of SMEs cite data collection, warehousing and reporting as their top spending priority, with another 18% investing the most in business intelligence and data analysis. It's no surprise that such a big spend is going toward data analysis, which serves to enhance machine learning and AI to deliver more accurate results. In a recent survey of worldwide retailers, 49% of business owners said they see AI and machine learning advances aiding in cost savings, followed by increased productivity (44%) and boosted revenue (43%).¹

So, how are Canadian retailers using big data in conjunction with AI to market their products, deliver more relevant offerings and—most importantly—deliver superior customer service?

Cost reduction and enhanced customer experience

Smaller storefronts and pop-ups within larger retail outlets provide shoppers with a more personalized experience, albeit in lieu of an extensive product selection. However, it's a trade-off many consumers and retailers welcome. Minimal merchandising allows retailers to put their bestsellers front and center, while the newfound retail space enables them to create superior customer experience. This could mean the installation of kiosks that provide for easy online ordering and additional product information or simply the addition of a lounge to create a more welcoming feel and customer experience.

Big data from inventory systems stored in the cloud enable retailers to bridge the gap between online and store sales. It enables better tracking of what sells best in the store so that merchandise is rotated accordingly. Canadian clothing retailer Bergstrom Originals shaved a full day per week off administrative tasks plus cut bookkeeping costs by shifting to a cloud-based inventory system that reconciled in-store inventory with their online sales.² Customers are also able to engage with their website while they are in the store, opening up an expansive world of sales.

Customized shopping tips and personalized service

Tulip, a start-up retailer in Toronto, is using big data stored on Google Cloud's machine learning platform to help its in-store associates’ interaction with customers.³ By accessing the mobile platform via a smartphone or tablet, salespeople can see a customer's past behavior to deliver a targeted, appropriate in-store interaction. They can also make relevant recommendations based on the consumer's prior purchases and preferences.

Similarly, L'Oreal Canada is improving its online customer experience using AI chatbots on approximately 1 billion websites, delivering product recommendations and dermatological advice customized to each user's skin type.⁴

Hiring workers based on intangibles

Waterloo, Ontario-based Plum.io helps tackle the tricky task of hiring a more diverse workforce. Using sophisticated AI algorithms, the company's software helps its HR professionals and recruiters make decisions based on a candidate's “talents" in areas like work ethic, teamwork, consistency, and leadership by sifting through countless data points in resumes and social media and looking for patterns.⁵ As a result, employers will know they are hiring individuals poised to take on leadership roles and deliver exemplary customer service.

Compile and combine big data insight

Harnessing big data could start with simple steps like using ad data for retargeting or, in the case of L'Oreal Canada, chatbot promotions. But the best initiatives will use online marketing and data collection alongside in-store interactions.

With American Express^®, businesses like yours are able to leverage insights on customer spending, which coupled with the knowledge on your own business expense patterns can help optimize your value chain. The result: Better efficiencies, cost savings and an enhanced customer experience.

 

¹ https://towardsdatascience.com/disruption-in-retail-ai-machine-learning-big-data-7e9687f69b8f

² https://www.vendhq.com/customers/bergstrom-originals

³ http://www.canada.ai/posts/tulip-partners-with-google-cloud-to-provide-machine-learning-solutions-for-retail

⁴ https://www.glossy.co/beauty/loreal-canada-expands-ai-ambitions-through-online-advertising

⁵ https://venturebeat.com/2018/06/13/plum-uses-ai-to-hire-people-that-never-would-have-been-discovered-through-a-traditional-hiring-process/

 

 

This article is intended for general informational purposes only and does not constitute legal advice or an opinion on any issue. It should not be regarded as comprehensive or a substitute for professional advice.