How to Build Long-Term Brand Loyalty With Your Big Data
With big data, you can observe various patterns and trends associated with your customers’ behavior to trigger their loyalty. So, in theory, the more data you have, the more patterns and trends you can identify. The trick is to do it effectively and correctly. Hopefully, the guide below will help with this.
Start by analyzing a few big data sets
Big data analytics can be time-consuming and costly, which is why it’s often more efficient to look at a few specific areas (such as the purchasing behavior of your least profitable market segment, for example), at least in the beginning.
Then turn your data into useful information
This is particularly important. The ecommerce development company Iflexion states that data itself “does not create a customer-centered culture.” It should be used to create a better user experience for the customer, which can only be achieved by linking the data with customer feedback loops.
For example, data analysis will enable you to identify …
- Your most profitable market segments.
- The proportion of customers making repeat purchases.
- The proportion of customers spending more than $10, $50, $100, $1,000, etc.
Analyze data for key performance indicators like the above and see how you stand with this against your competitors.
And how does this help you build brand loyalty?
Well, firstly, let’s take a look at operational efficiency – the level at which a business can sell products or services for the lowest cost while maintaining high standards in terms of quality and customer service.
In regard to ecommerce, one way to measure operational efficiency is to analyze the speed of your customers’ purchases. There are many ways to look at this. For example, for shoppers on your website, you might look at the time between when they …
- Arrived at the website and made a purchase.
- Viewed a product or service and added it to a shopping cart.
- Added a product or service to a shopping cart and purchased it.
- Inquired about a product or service and received an answer.
These big data analytics can show you the typical pitfalls in your customers’ journey:
- Is there anything that could be improved?
- Is there a particular process that frustrates your customers?
- Are they taking an unusually long time to decide whether to buy some of your products or services?
Or maybe they aren’t navigating your website as quickly as they should be (e.g., because the ‘next’ button is too small or isn’t displayed properly)? Worse, if they can’t find the information they need, they might be defecting to a competitor’s website, which can also be bad for your website’s SEO.
Optimize customer experience
The more data you analyze, the easier it will be to establish the causes of any failures or issues that might be compromising your customers’ experience. With a more comprehensive understanding of your customers’ attributes and behavior, you can also optimize their experience through targeted marketing to increase revenue per customer.
Optimize your pricing
Use algorithms to monitor your competitors’ activity and swiftly adapt to new market changes. This will make it easier for you to decide when to adjust your prices to maximize revenue. …read more
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