The retail industry has changed a lot over the past few years, and the pace of change has accelerated. Customers are always on time, and the multi-device form factor is what they use to browse. More and more online shopping is now merging with traditional offline shopping, customers expect a seamless experience between the online and offline worlds, everything should just work faster.
5 challenges of customer-centric e-commerce and retail.
A recent Qubit study surveyed retail customers and asked them what would ensure they would make more purchases on mobile devices. Here are the top five reasons customers cited:
- If browsing is faster/easier.
- If only it would be easier to find what I’m looking for.
- If only it were easier to spot new products that I love.
- If payment is easier.
- If I’m not distracted.
Online retailers have tried to develop capabilities in these areas but have repeatedly found the investment in building such infrastructure and product solutions too high, but due to cloud platform vendors and various AI and ML With product offerings, even small retailers have the potential to close some of these gaps in the customer experience, creating a more enjoyable experience for customers, which leads to more sales.
Solve e-commerce problems
In this post, we’ll see how to address each of these challenges:
1. Faster browsing
Using cloud services will result in a faster browsing experience compared to a single server for traffic. This results in faster response times as cloud hosting platforms use clusters of servers for load balancing. The more rich media images, videos you plan to use the higher the benefits you will get from using cloud hosting (in some cases, this is up to a 60% improvement). In addition to a faster experience, cloud hosting offers a higher level of security (compared to what you can usually provide on your own), and the ability to scale seamlessly as your traffic grows.
2. Simply find what you want
We are busy and always on the move, we see a great dress and want something like that. Thanks to various products that use image processing and pre-trained machine learning models to recognize and classify images. Integrating these products into your retail workflow will mean you can have the experience where someone snaps a piece of clothing they just saw in a store and you can show them a similar product from your catalog. Some of the large cloud computing vendors offer products as part of their AI/ML offerings to enable this.
3. Easier to discover new products
Displaying related, complementary product suggestions helps your customers discover other products they might be interested in. With a cloud platform, you can create and train a machine learning model to bring up relevant product recommendations during a customer visit. By using profiles, customer history data, browsing history, you can also customize recommendations and also adapt to changes in the environment, such as changes in offers, sales, product catalogs, etc.
4. Easier to pay
Most cloud platform providers offer payment solutions that you can integrate into your workflow. Rather than developing your own payment solution, we strongly recommend that you integrate it with your cloud provider’s solution. It’s also important that your payment solution works with different currencies if you’re expecting customers from different countries, it’s worth testing for this use case (e.g. ordering from another country).
5. Don’t distract customers
With so much going on in our lives, this is probably the hardest thing to fix, maybe an interesting news article pops up while your customer is busy leaving halfway through the buying workflow. To try and solve the problem of customers getting distracted and leaving the buying process, you can:
- Ensuring an end-to-end shopping experience requires as few steps as possible (multiple testing, including A/B testing).
- Send a notification when an item has been added to a customer’s basket, but the purchase has not yet been completed.
A wide range of cloud services and advances in artificial intelligence and ML are making it easier for the retail industry to create richer and more engaging customer experiences. Experiences that required significant investments in servers, infrastructure, and data scientists can now be achieved at a fraction of the cost (investment, time, and manpower).
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