Conversational commerce in retail
What is conversational commerce in retail
We’ve previously gone into detail about everything you need to know about conversational commerce. But that’s conversational commerce as a concept. And as concept, it’s subject to slight variations across industry-specific implementations. Conversational commerce, as it refers to retail, implies the integration of all systems necessary to facilitate the creation of complete conversational customer journeys over messaging channels that occur in real time.
A very simple example of this would be conducting a full transaction over a chat app – instead of through your web store or shopping app.
How is that even possible? What does conversational commerce look like for retailers and eCommerce companies? And how can you build conversational customer journeys, and know whether you’re even doing it right?
Find out all this and more.
The rise of conversational commerce in retail
In 2021, the global AI commerce market was estimated to be worth over $6bn USD. This total is expected to grow yearly, hitting a compounded growth rate of 23.6% by 2030.
Keep in mind, these estimates come from a time before anyone was savvy to ChatGPT and all the things you can do with it.
This growth is fueled by a few key factors.
Businesses can reduce customer service costs by upwards of 30% using chatbots. This is because conversational chatbots can handle the most common customer queries. Add machine learning to that, and there’s virtually no end to what a conversational chatbot can do for customer service.
This is important because customers get frustrated if they’re made to wait. In fact, according to a 2020 survey conducted by Drift and Heinz Marketing, the greatest cause of frustration among customers were unresponsive brands. Compared to the previous year, the number of customers left frustrated by irresponsiveness surged 5.7x.
According to the same report, 46% of customers expected responses from chatbots in under 5 seconds. But 43% said they expected the same using online chat.
And 50% surveyed said the most important thing for them using conversational commerce was getting quick, detailed, expert answers.
Conversational commerce systems can satisfy these customer demands, making for good CX, higher CSAT, and increased loyalty.
Creating a unique retail experience for every step of the customer journey
The underlying technology of conversational commerce facilitates hyper-personalized customer journeys.
Conversational commerce technologies can quickly access and analyze customer data across various touchpoints to:
- Provide proactive customer service: Using contextual data from various sources, retailers can predict why customers are contacting them. This could be due to a late delivery, or providing item information following delivery just in case anything is wrong.
- Offer relevant product recommendations: Customers can be turned off by businesses that offer irrelevant products. Conversational commerce technologies can immediately fetch and analyze customer browsing and purchase history to recommend complementary products.
- Cross-sell and up-sell: Goes hand-in-hand with offering relevant product recommendations and complementary products. But with the difference of being presented as a personalized recommendation versus a lifeless “customers also bought:” section of your checkout.
- Complete checkout: Thanks to payment integrations, customers can complete purchases within the same chat app they began their customer journey. It’s fast, convenient, and safe.
Because conversational technology can instantly access and analyze customer data profiles, shoppers can enjoy hyper-personalized experiences that are quick and convenient.
Conversational commerce retail benefits and elements
Conversational commerce excels at common retail-specific use cases. Starting with:
Conversational commerce reduces cart abandonment by essentially getting rid of the cart. Purchases are completed within the app conversations are started in.
This eliminates the need for a buyer to move from browsing windows towards carts, then going through all the steps needed to complete a transaction.
Instead, transactions are quick and easy with the push of a button, getting around the common customer journey sticking point that results in cart abandonment.
Retailers and eCommerce companies can also leverage their conversational channels to re-target customers with products left in their carts via conversational channels within which they can quickly and conveniently within the same channel.
Booking deliveries and returns
Deliveries are a common customer service issue. The problem with this is that retailers don’t handle shipping – but they do handle unhappy customers demanding to know when they can expect their package.
With conversational commerce systems, retailers can integrate with shipping companies to pull data and provide customers with instant delivery status updates.
And this goes both ways – meaning returns. Customers can schedule a pickup and return via the same retailer-integrated delivery service by chat.
This makes for a far smoother customer experience than dealing with the retailer and delivery services individually.
This allows shoppers to browse entire product catalogs without leaving the chat app – where they can even complete their purchase.
Transactions and payments
This removes friction from the checkout process, reducing cart abandonment, ultimately increasing sales. And this is achieved in a way that improves CX, which results in heightened, longer-lasting loyalty.
How to start with conversational commerce in retail
Choose a conversational commerce platform
The first step is to consider which conversational commerce platform offers the features you need to provide complete conversational customer journeys.
Start by looking at what you already have integrated with your systems and whether these can be used with your conversational commerce platform.
Specifically, consider whether your existing systems can “speak with” your new conversational commerce platform. Else, you run the risk of relying on incomplete customer data profiles that don’t get populated from other customer lifetime touchpoints. This results in poor CX.
Be mindful of payment processing capabilities, as well. It doesn’t help to build complete automated conversational customer journeys just to find out you can’t accept payments in your jurisdiction.
Choose the right channel
Retailers commonly focus on developing conversational commerce capability for the channels that have the highest customer engagement.
Turns out this isn’t the best approach.
While channel engagement is an otherwise important KPI, channel functionalities play a more important role in conversational commerce.
The optimal approach is to strike a balance between customer habits as well as channel functionality.
For example, developing conversational commerce capability for a channel that doesn’t facilitate product catalogs or simple in-app payments may not be an optimal use of resources.
Define your conversational commerce strategy
Consider what part of your retail business your conversational commerce system will cover and develop in that direction.
This should factor in the basics like channel capabilities and tone of voice, but also more complex issues – like how conversational commerce will work with your sales and marketing strategy.
Will the role be more focused on resolving customer service issues? Is the idea to boost sales? Or guide customers through common sticking points in the customer journey? Or all of the above?
Design your conversational commerce strategy as a complement to your existing strategies to start out. As your system learns from more interactions, it will be able to handle a wider range of tasks.
Plan a conversational flow
Identify at which stage of the customer journey conversational interaction begins. Start planning how your chatbot will interact from this point and the actions it takes.
This results in a guided customer journey optimized to fit your strategy.
Train your chatbot
Starting out with a basic set of responses and actions will yield basic results. Conversational chatbots need to be trained to understand a broader sample of customer intents.
This is achieved by programming chatbots to understand several phrase variations for each customer intent.
Continuous training is aided by equipping AI with machine learning to understand new intents.
Monitoring interactions is also crucial since it helps identify and address any problematic areas where customers may be dropping off.
Test your conversational commerce solution
Before unleashing your conversational commerce solution, take a test drive of your solution as a customer. This will let you identify areas of improvement and shake out any bugs.
It also gives you the unique opportunity to experience your customer journey from a shopper’s point of view. This is a valuable opportunity to evaluate and potentially further optimize parts of your customer journey.
Conversational commerce retail KPIs
Starting out, it can be difficult to know what kind of impact your conversational commerce system has on your business. Here are some helpful KPIs to look for specific to conversational commerce in retail.
- Conversion rates: How many conversations are resulting in completed customer journeys, i.e. resulting in a sale
- Cart abandonment rates: Monitor how many customers drop out of the customer journey before completing a conversion on both your conventional and conversational sales channels.
- Goal completion rates: Depending on how you use your conversational commerce system, what comprises a “goal completion” may vary. For some use cases, the goal could be to just resolve customer service queries, for example.
- Customer satisfaction scores: Ask customers for feedback in the same chat by sending a survey. Alternatively, you can simply ask customers to rate their satisfaction across key CSAT components with a 1-10 rating.
- Average response time: Monitor the time it takes your conversational system to reply to customer enquiries and collect averages across customer service teams to see the impact on this crucial customer satisfaction stat.
- Average conversation length: This KPI is a bit of a double-edged sword. It can indicate either fantastic engagement or conversational inefficiencies. Again, consider what your system was designed for – if it’s fast customer service, this stat should be on the shorter time. But if your conversational commerce system is designed to create engaging customer journeys, then longer times may be better.
Several conversational commerce success KPIs need to take into account the purpose of your conversational chatbot within your sales strategy. What one business case may consider a success, another may see as a conversational system under performing. Consider your case when gauging across these metrics.
The next step for retailers and eCommerce companies
Trends show that commerce is moving towards messaging apps. Customers are looking for the personalized feel of an in-shop experience delivered over a single channel from the comfort of their own couch.
Retailers and eCommerce companies sell more, faster, with comparatively lower overhead than it would require to staff teams around the clock.
Getting started in conversational commerce isn’t even complicated.
In order to be ready for the shift towards more conversational commerce, retailers need to start developing their conversational channels. The ideal starting point is to automate customer service enquiries with a machine learning AI conversational chatbot.
This way, you’ll teach your chatbot how to understand the most common customer intents, while machine learning will help it understand more and broader intents over time.
And in time your system will evolve into a conversational commerce system capable of managing entire customer journeys from entry, past conversions, to customer service – and back again.
Start your conversational commerce evolution
Talk to our experts to help you kickstart your conversational commerce evolution.