It’s hard to ignore the dramatic shift that’s taken place in retail in the past 18 months, with over 35% of UK retail sales now happening online. This trend has forced many retailers to adapt on the fly and innovate to compete. As society begins to reopen, here are the top three retail digital transformation trends taking the world by storm.
As online retail soars, companies must employ evermore sophisticated tactics to capture and convert their ideal customers, while ensuring physical stores remain relevant and provide a worthwhile experience.
With consumer behaviour now heavily weighted towards speed and convenience, retailers have a renewed focus on joining the dots in the customer journey to deliver the right product, in the right place, at the right time.
While none of this is rocket science, many retailers still have work to do to ensure they have the right technical capabilities in place to adapt and meet customers where they are.
Read on to discover the top trending retail tactics in 2021, alongside our post-pandemic predictions.
Hyper-personalisation is a growing retail trend that’s here to stay; but what does this mean for businesses and customers? What does the future look like? And, most importantly, how do you deliver it successfully?
The possibilities are endless - from walking into a store that automatically adapts its digital signage based on a returning customer’s profile, to ‘trying on’ alternative hairstyles at a salon before committing to a new look using VR technology.
The more relevant data you’re able to collect, the easier it will be to segment your customer base and provide intelligent recommendations across products, services, and tailored promotions.
In order to provide a strong and consistent customer experience, you may wish to collect data on the following:
Segmenting your customers based on age, gender and location enables you to recommend specific products and/or services, map the customer to their nearest store(s), and promote regional offers.
Monitoring customer behaviour over time can be truly revealing. Whether you’re documenting a customer’s website journey from A to B, or simply determining how they arrived at your site in the first place (direct vs organic traffic), you can leverage this data to create seamless journeys and hyper-relevant experiences.
Collecting customer information on previous purchases, such as product/service type, Average Transaction Value, sizing (if applicable), percentage of items returned, and usual payment method all help to build up a bigger picture and can help you predict how they might interact with your business in future. As a result, you’ll be able to deliver highly relevant experiences to meet their needs.
Mapping your customers across online and in-store interactions can help you determine when and where they’re most likely to browse vs make a purchase. You can harness this data to deliver the right message, in the right place, at the right time - gently steering the customer towards the desired outcome.
While these are just a handful of ways you can use data to enhance the customer experience, new use cases for hyper-personalisation in retail are continually emerging - helping retailers to upsell, cross-sell, and drive revenue.
Download The Retailer’s Guide to Data Maturity to find out how we can help you expand your data capabilities, improve performance, and drive revenue on Google Cloud.
2. Omnichannel customer experience strategies continue to dominate
Whether you’re a frequented grocery store or a luxury fashion house, creating an omnichannel experience for customers has never been more prolific in the retail sector. And yet, not every organisation does it well.
The devil is in the data, and creating a truly omnichannel experience relies on joining up to the dots from the very first customer interaction. Having immediate visibility across what a customer is doing, where they’re interacting, and when they’re most likely to be influenced is like gold dust.
Once you have the technical capability to glean these customer insights, the hard work doesn’t stop there. Ensuring your workforce is fully equipped to monitor, analyse, and respond to drive engagement and deliver the ideal outcome, consistently, across every interaction is crucial to your data strategy.
At Appsbroker, we can help you move away from your existing legacy system and provide the basis for a Modern Data Platform, bringing all of your data sources together to facilitate an omnichannel customer experience.
We’ll also provide you with ongoing training on the new platform to help you become data-driven and meet your customers’ needs wherever they are on their journey.
If the phrase ‘machine learning’ brings robots and Sci-Fi films to mind, then you might be surprised to learn that ML has some highly practical use cases in retail. In fact, our 2020/21 UK-based Machine Learning Insight Report revealed 39% of businesses are ramping up their ML efforts in light of the pandemic to improve the customer experience and drive revenue.
Predicting demand is the crux for many organisations; whether that’s retail sales or manufacturing product volumes. Obtaining accurate predictions is a simple way to deliver efficiencies using machine learning, leading to increased sales and customer satisfaction, as well as agility.
Personalisation & Product Recommendation
Generating tailored product recommendations, offers and experiences for customers is key to maintaining a personalised touch across e-commerce, traditional retail, financial services, and more. The result is increased sales and customer satisfaction, greater customer engagement, and an overall stronger customer experience.
Security & Fraud Detection
Fraudsters employ relentless tactics to make money from unsuspecting businesses. Modern machine learning systems can include monitoring, automated retraining and an MLOps framework for automated redeployment. Automation can enhance your fraud detection systems to reduce loss and react to suspicious activity on the spot.
There are growing use cases for image processing in retail, enabling you to automate typically manual processes, scale up image processing capabilities, and provide new and exciting ways to engage with customers. For example, you could deploy a product recommendation tool allowing a customer to upload an image of a sought-after item, generating a tailored product recommendation.
Natural Language Processing
Natural Language Processing (NLP) allows retailers to interpret human interactions through automation, email handling and smart assistants. The ability to automate this process and make rapid decisions can help you reduce costly human interactions (such as live agents), gain unique insights on-demand, and harness this information to iteratively improve the customer experience.
At Appsbroker, we can help bring your ideal machine learning use cases in retail to life and get your people up to speed to maximise ROI.
Read our latest retail case studies now to discover how we’re helping organisations like yours drive revenue through hyper-personalisation on Google Cloud.
Data maturity occurs when you combine clean data sets, real-time insights and automated decision-making to deliver a strong customer experience and true business value. The outcome should be mutually beneficial for you and the customer every time.
Hyper-personalisation, omnichannel customer experience strategies, and machine learning can all be exciting and impactful in their own right. However, to ensure long-term success, your organisation needs to stitch all of its customer instances and capabilities together into a Modern Data Platform.
When you take away all of the bells and whistles, it all boils down to the data. At Appsbroker, we can help to ensure yours is safely governed, distributed, and easily accessible from the get-go to promote data literacy across your entire business for years to come. We’ll also help you bring your people up to speed from executive through to board level to educate them and promote adoption.
Ready to unlock your data potential? Download The Retailer’s Guide to Data Maturity today to find out how we’re helping businesses drive innovation on Google Cloud.