As a consumer, you have at least ten brands to choose from when making a purchase. The increasing number of online stores have given consumers a lot more choice than before. On the flip side, what it has resulted in is being able to reach the right audience and turn them into customers.
As a result, you can see brands running endless ad campaigns on social media and the search engine.
While most of them can drive traffic to their stores, the conversion rates are mostly on the lower end.
The reason? Either too broad a targeting that leads uninterested shoppers to their store. Or too narrow a targeting that results in not being able to reach as much an audience.
This is where data comes in. More specifically, customer segments and analytics.
Getting to know your shoppers with customer analytics
When you started an online store, you created a customer persona assuming certain demographics would be interested in purchasing your products. You also did a little research on where you could reach this audience, adding that into the persona information. Great job!
But that’s just doing the groundwork because the market is always changing. The platforms they’re active on, the content they engage with, and where continually changes owing to seasonal trends, market shifts, and more.
This is where digging into your customer data comes into play to optimize your personas to remain up-to-date at all times.
Customer analytics is a branch of eCommerce analytics that focuses on understanding a shopper’s behavior. It pulls in key factors like what demographics (age, gender, location, etc.) the shopper falls into, where they discover your brand, what kind of campaigns they engage and converts on, and more.
It then uses this data to enhance your customer personas by creating “customer segments.”
So basically, you’re moving beyond the general demographics of the shoppers who come to your store. Now you’re focusing on what brings them to your store, what motivates them to complete a purchase, and, more importantly, the revenue you’re able to generate from them.
For example, when you notice a group of shoppers who engage with your brand only when your products are on discount, they’re the price-sensitive lot.
Now there will be shoppers who engage with you only when you release a limited edition product. You can segment them into a category of high-value customers.
To drive the point home, let’s take another example. You notice a group of shoppers actively browsing products on your store, adding them to cart but abandoning the purchase always. You know these are cart abandoners.
What you see here is the data you already possess. Just fitted into your existing customer personas to reflect purchase behavior and motivations.
Why should you focus on enhancing your personas with customer segments?
According to a survey, more than 74% of online shoppers prefer to engage with brands that personalize their journeys. In fact, 89% of these customers switch brands after a poor customer experience due to the lack of personalization, leading to a 20% loss in annual revenue.
With customer segments, you go beyond just demographics to offer a more tailored experience. Right from ad campaigns to emails and your overarching strategy to entice customers goes from age brackets to their spending power and addressing their purchase motivations.
- Personalization leads to an increase in conversion rates by a minimum of 3.4%
- Personalizing your ad campaigns for higher context leads to increased AOV.
- Increased AOV leads to higher retention rates and customer loyalty.
- A 5% increase in retention leads to a 25-90% increase in profits.
Simply put, your customer data is worth a lot more sales, revenue, and profits when used in the right manner.
But what’s stopping eCommerce businesses from tapping into this opportunity?
The status quo of customer data in eCommerce
Most eCommerce businesses have marketing and advertising campaigns running on multiple platforms: social media, email, search engine, and more. To gather the data coming from all these campaigns, they’re also using as many marketing tools.
With this approach, brand owners and marketers can see which marketing channel drives sales and which isn’t. But what about which platform is getting them what kind of customers?
More often than not, this information is derived either based on an assumption on the ‘type’ of the run’s campaign. At other times, one digs into what Google Analytics has to say about the source of traffic and consumer search intent. But in the end, moving from what tool to another or going through endless guides on using Google Analytics to pull out a distinct characteristic of shoppers becomes overwhelming.
As a result of this, you can see most eCommerce brands shying away from creating holistic customer segments, leading to the loss of many opportunities to sell more.
Turning customer data into actionable needs an aggregator.
One way of digging into data to understand who your shoppers are is by setting up advanced Google Analytics for eCommerce. Then add a layer of insights gathered from your email marketing tool, Facebook Insights, search console, and other marketing tools you may be using to run campaigns.
More often than not, this is either done by downloading reports from each platform and discussing it over a meeting. Or by collating all the data into excel spreadsheets to conclude. Both of which are methods that are prone to human error.
That’s where having an eCommerce analytics tool that acts as an aggregator for all your data comes into play. Here’s what eCommerce store owners and marketers need to look at to be able to derive actionable customer data:
- Capturing a holistic view of marketing and advertising campaigns: Running omnichannel campaigns is a must for reaching out to your audience and promoting your products. But being able to optimize budgets on wasteful campaigns that don’t result in sales requires capturing all your data and campaign performance on one dashboard.
- Identifying customer purchase behavior: Every online shopper is different, and the reasons to complete a purchase are as varied. An eCommerce analytics tool can give you the ability to assess who is interacting with your campaigns and who is actually converting on them, and why.
- Segmenting customers based on interaction: While some visitors choose to subscribe to your store updates, some may make a purchase, and others would leave without completing the checkout process. It’s important to capture and categorize these shoppers based on their behavior to re-engage them with personalized campaigns. For example, cart abandoners, repeat customers, VIP customers, loyal customers, and more.
- Identifying the right channels to reach different segments: In addition to the customer segments, the analytics tool should also highlight where you’re capturing the most customers. Right from the platform to the placement of your campaigns, knowing where you’re able to grab eyeballs is the trick to driving more traffic and conversions from your target audience.
With more and more brands going online, it’s not just the competition for customer attention that has become challenging. Being at the right place at the right time is getting tricky too. Spreading yourself too thin leads to increased customer acquisition costs that result in overheads when added to other eCommerce operations to keep the business running.
Knowing who your customers are, what category of purchase behavior they fall into, and what their motivations are to make a purchase helps you allocate your resources (both time and money) in the right direction.
Are you still relying on social platforms’ targeting options, or do you really know who your customers are?
About the author
Vanhishikha Bhargava is the Head of Content and Partnerships at RevTap, an eCommerce analytics solution that enables stores to simplify their data. With customer segments, product analytics, and performance metrics collated into actionable reports on a unified dashboard, the business intelligence tool aims at helping online businesses grow with data-centric strategies. You can connect with her here.