Businesses that use data-driven marketing strategies experience 20% more return on marketing investment (MROI) compared to those that don't, a study by McKinsey & Company found eCommerce businesses often have to focus on two key metrics for their marketing campaigns - traffic and conversions - both equally important.
These metrics can help identify opportunities to streamline strategies, optimize performance, and drive sustainable growth.
In this post, we will share how you can maximize your overall profits by strategically converting traffic into conversions with predictive analytics.
Understanding eCommerce Traffic vs. Conversions
More often than not, eCommerce businesses get a lot of traffic that does not necessarily translate into sales. There could be several reasons for this:
You’re not matching the search intent
The content and user experience (UX) on your website doesn’t match customer needs
Your site speed is too slow
It is important to understand that traffic can be from buyers who are too early in the buying journey. Think about it - most online purchases begin with a simple Google Search.
However, it’s rare to complete a purchase within the first store visit. Most conversions are from those who are nearer to the middle and bottom funnel.
And that is what makes the difference - attracting the most engaged, ready-to-purchase set of your prospects at the right time.
Common Conversion Challenges for eCommerce
Here are some bottlenecks most eCommerce stores face when trying to improve their overall profits.
Poor targeting
Usually, eCommerce marketing campaigns, be it through Facebook or Google or on marketplaces, optimize for traffic. This traffic may or may not be relevant. Getting the right traffic is everything for your eCommerce brand.
Without the right targeting, you may still get high traffic to your storefront, but this would not lead conversions. Visitors may find the products not relevant and may quickly leave without making any purchases. This usually happens when your campaigns are generic and not customized to the target audience.
For example, you run a premium women’s clothing eCommerce brand, but your ad campaigns target women in general but not by demographics or behavior such as their income group, their frequency of online shopping, etc. This may lead to underwhelming responses and subpar results.
Lack of personalization
Many brands think big data is meant for big retail brands that can afford an in-house team. In contrast, the smallest businesses have the means to access and conduct data analytics for business.
eCommerce platforms like Graas' track and give you access to consumer behavior data, which you can use for informed decision-making.
Additionally, personalized recommendations encourage the customer to return to your store. It helps define how long your visitors are engaged on your site, which in turn translates into greater sales and reduced customer acquisition costs.
Store browsing habits can generate valuable data for running various campaigns, through smart recommendations. You can also automatically create the most suitable campaigns for your marketing objective. The data-backed approach combines the appropriate ad types, objectives, and audiences to launch campaigns in line with the budget.
Friction in the buyer's journey
Today's shoppers interact with brands across numerous channels before buying.
The customer may see a social media advertisement, go to the website, get a retargeting advertisement via email, read product reviews, and inquire on price comparison sites before buying the product. Because of this complicated consumption process, it is hard to pinpoint the particular touchpoint’s value that an attributable marketing campaign exerted on the overall sales conversion.
Also, different customers may have different routes to purchase, increasing further attribution problems. Organizations must be able to follow and investigate these paths in order to find out what contact points are most effective and at which stage of the process.
How to Optimize Conversion Rates - the Smart Way
Conversion Rate Optimization (CRO) is the process of making small, methodical tweaks to your website or marketplace presence in order to improve the rates of conversion.
This could be anything from changing the CTAs to redesigning your entire layout. The goal is to find the changes that make the biggest difference in your sales.
Let’s take a look at a few data-backed and easy ways to do this.
Identify traffic sources and user engagement
Understanding where your visitors come from and how they interact with your site is crucial for optimization. By leveraging advanced analytics platforms like Graas, you can track key metrics such as:
Time spent on site
Page views per session
Bounce rates by channel
User flow and navigation patterns
Optimize D2C pages or marketplace listing
Optimizing your product listings for each marketplace is one of the most fundamental strategies to boost revenue.
Whether it's Amazon, Lazada, or Shopee, each marketplace employs a unique search algorithm and ranking criteria to determine which products appear first to their audience.
To maximize your visibility and, consequently, your marketplace revenue, it's crucial to tailor your listings to meet the specific requirements set by marketplaces. This should include:
Identifying the most relevant and high-traffic keywords for your products
Compelling and true product descriptions
High-resolution images showing your product from multiple angles and follow the guidelines of each marketplace to use images of appropriate size
Competitive pricing
Apart from these, you should also make changes based on upcoming seasons and popular occasions like BFCM or Double Day Sales.
Improve checkout process
The average online shopping cart abandonment rate worldwide is around 70%.
That’s a lot of lost potential conversions. But a few simple changes can help improve this. Be it simplifying the form fields, reducing the number of steps in your checkout process, incorporating an abandoned cart email campaign, or making your site mobile-friendly - these small changes can have incremental benefits to your bottom line.
How to Leverage Predictive Analytics
Predictive analytics takes unstructured eCommerce information and helps increase sales by turning that information into useful insights. Here’s how to leverage this invaluable opportunity across your most essential business functions:
Trends and demand insights
Effective strategies to estimate future demand include studying sales history, consumer search data, and seasonal trends. Utilize tools like Graas to decode which product categories are slow to sell and which items are likely to become best sellers.
This allows you to predict changes in the market and modify your product range in advance.
Customer behavior analysis
Today's shoppers interact with brands across numerous channels before buying.
Analyzing customer journeys, purchase frequency, and online activity can provide insights about their next buying action.
By examining factors like the number of abandoned shopping baskets, duration of particular pages, and previous transactions, you can provide a better shopping experience tailored to their preferences.
Inventory management
Tune inventory quantities using demand forecasting techniques that work for all product lines and unique seasons. Such knowledge helps avoid stock-out and overstock situations, thus minimizing inventory costs.
Marketing strategies
Target customers more effectively by predicting their likelihood to respond to specific campaigns or promotions. Use behavioral data to identify the best times to send marketing messages, optimal pricing strategies, and the most effective channels for different customer segments.
This enables personalized marketing campaigns that reach customers when they're most likely to convert.
Wrapping Up!
Today, customer purchase journeys have become non-linear in nature as buyers deal with brands through different touch points before they make the final decision.
This complex, multi-touch marketing demands a deeper understanding of campaign effectiveness. This is where attribution becomes crucial.
Maximizing budget allocation with accurate, data-backed marketing attribution to identify which channels and campaigns generate the highest ROI is the smarter budget allocation.
Using advanced eCommerce analytics tools like Graas, you can streamline your analysis processes, gain deeper insights, and make data-driven decisions that drive tangible results.
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