Predictive Analytics for Retail Industry Challenges

In this current climate, customer loyalty and retention has become more difficult to earn. They have hundreds of options available and high expectations from each business they deal with. These high customer expectations are creating new challenges for businesses.

Alongside the increase in customer expectations, the eCommerce space is under huge monetary pressure. Rising prices, increased shipping costs and supply chain issues, growing competition, and rising marketing costs are all taking their toll.

Overcoming these obstacles takes time and effort, but there are practices that make it easier. Specifically, predictive analysis provides eCommerce businesses with the insights they need to make better decisions.

Using your customer data and employing machine learning, alongside other techniques, allows you to understand your customers. Analysing their previous behaviours will give you a good idea of how they might behave in the future.

However, understanding what challenges lie ahead of you and what customers want is the first step. 

Challenges faced by eCommerce businesses

Over the last few years the eCommerce space has experienced an incredible amount of change. It is a far cry from where it was even just a decade ago, not to mention its acceleration in growth after the pandemic. Alongside the shift to mobile devices for shopping and the growth in digital marketing, eCommerce’s market share continues to grow.

But as the eCommerce scope has changed, so too has customer behaviour.

Emphasis on Multichannel Experiences

Customers that shop across multiple channels are seen to have a 30% increase in lifetime value, compared to single channel shoppers. This is an indication of how customers are beginning to behave.

There is a massive emphasis on the customer experience with businesses these days. With so many devices and channels available, customers are less likely to be communicated with via just one channel. As a result your communication strategy  needs to include touchpoints everywhere they are.

Excellent experiences for customers across all channels is where you need to perform and put weight towards. Other companies are providing these experiences. So if you’re not you will lose out.

Seamless experience expected

If you operate both brick and mortar stores and an eCommerce site, you’ve got your work cut out for you.

Customers expect the movement between online and in-store activity to be a fluid transition. Systems should – as far as your customers are concerned – just talk to each other.

Someone who shops with you on a regular basis online expects to be treated as a regular customer in your physical store too. And vice versa.

Having your customer data stored in one, centralised space can aid businesses in providing these experiences. It’s really important that you understand your customers and know how they interact with your brand. If they made a purchase online then the systems in your brick and mortar stores should know that as well.

Overall, the feeling that shoppers get in store should be replicated online.

Loyalty in a saturated market 

There is no denying that the eCommerce space is absolutely flooded. If you can think of it, multiple stores are probably selling it. This makes the room for error by your business tight. Put one foot wrong and you could see a lot of your customers move elsewhere.

Currently, price is what drives sales in eCommerce. To survive in the industry, you have to do more than just have the deepest discounts. Long term success is dependent on retention and loyalty and the only way to achieve this is by adding value in other ways.

Weaning your customers off of low prices through tailored promotions and personalised loyalty programmes shifts the perception of value away from just the financial. 

After all, customers expect that every single interaction they have with a business is both relevant and personalised to them and their tastes. Living up to these expectations will create a loyal customer base. And loyalty is the way to win.

The use of your customer data is imperative to your success in providing that personalised experience. Transactional data, browsing history, and general personal tastes should all be understood before reaching out to a customer. 

It’s all about showing them you know them and guiding back down the sales funnel with products they are actually interested in. You’ll find that your customers will keep coming back.

Siloed customer data

Providing the multichannel experience that customers crave starts with your customer data, how you treat it, and how you use it. But with so many channels to offer it’s easy for your data to become siloed.

This is where you will begin to run into problems. Every facet of your marketing department should be working together. Customers will become annoyed and overwhelmed with generic messages repeated on every channel. Having your data stored in one central location that can be fed into each channel will allow you to create a personalised experience.

A customer data platform, or a customer data and engagement platform will help you drive clear, relevant messages. 

How Predictive Analytics helps ecommerce businesses

The challenges above are not impossible to combat. They are something that every business in the industry faces. There are ways to overcome them.

An eCommerce business can benefit massively from predictive analytics. Using data, machine learning, and other modelling techniques can allow you to make predictions on customer behaviour. 

Understanding its benefits and using it properly can open up a goldmine for your business and contribute to creating an unbeatable customer experience.

Predict what your customers want and keep them returning

Retaining your customers is far more valuable in the long run than constantly acquiring new ones. To keep them returning you need to know how to communicate with them, and what to show them.

Putting something in front of them that they have never shown interest in, is pointless and annoying. Rather than returning to the sales funnel, you will likely push them in the opposite direction.

Every single interaction you have with a customer should be used to get to know them better. The more data you gather and understand, the more it will filter into your predictive analytics efforts.

Once you can start to predict accurately based on previous interactions, you can start to put relevant messages and products out in front of your customers. And once customers realise what you’re sending is relevant, they will be far more likely to stay with you.

Predict customer churn to retain them

Customer churn is an issue that most eCommerce businesses face. Predictive analytics can be used to identify customers at risk of churning.

Customer behaviour and transactional data can give you an indication of customers that are becoming dormant. You will see that they are interacting with you less, or not making purchases with you anymore.

Understanding these things means that you can act in a timely manner and potentially rescue a churning customer for your business.

Segmentation to predict patterns in customers’ behaviour

Treating all of your customers as if they are the same will only bring you bad news as a business. You need to understand how your customers interact with your brand and their activity in general. Knowing this information means you can group similar people together and create relevant campaigns for them.

What predictive analytics and machine learning can do here is make the segmentation process much more efficient. You can automate the process by creating segments based on characteristics and previous behaviours you have identified. 

You will start to understand how each segment responds to different things and what leads them towards completing a conversion.

Don’t Let Up

Predictive analytics will help you overcome challenges that you might be facing, especially when it comes to engaging your customers. It may be a slow burn at the beginning, but remaining consistent with it is the key to its success.

To learn more about predictive analytics and customer engagement, get in touch with the team to request a demo.