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Making the Most of Your Analytics Reports

While analytics can uncover trends in products and customer behaviors that lead to greater sales and increased profitability, data and analytics do absolutely nothing without action. However, generating a return on investment (ROI) from your analytics means you’ll need to set up success metrics.

Success Metrics

Many of the larger retail chains and small businesses use the following metrics below to drive their analytical decision-making to help their business’ grow:

  • Average Order Value (AOV) - (Revenue / Orders): This is the amount of revenue you can expect for each new order that comes in.
  • Cost Per Impressions (CPM) - (Ad Spend/(Impressions/1000): This is most commonly used to measure the rate you would pay for an online banner ad campaign or other online advertising campaign. An Impression refers to the times the ad is served on a webpage (how many times the ad is seen).
  • Cost Per Click (CPC) - (Ad Spend / Clicks): This is most commonly used to measure the rate you would pay for a search engine ad campaign. CPC can also be referred to as PPC (Pay Per Click).
  • Cost per Acquisition (CPA) - (Ad Spend / Orders): This is most commonly used to measure the rate you would pay for a new order or customer. CPA is often used when measuring the rate you would pay an affiliate for referring an order to you.
  • Cost of Sale (COS) % - (Ad Spend / Revenue): This is the portion of your revenue that goes to your ad spend and is measured in %.
  • Conversion Rate - (Clicks / Orders): This is the rate at which customers convert from your landing pages. You can look at this metric for each individual advertising campaign or for your site as a whole.
  • Revenue Per Click (RPC) - (Revenue / Clicks): This is the amount of revenue you can expect for each click you receive to your site.
  • Customer Lifetime Value (LTV): This is the projected revenue that a customer will generate during their lifetime. For a full explanation of how to calculate LTV for your online store, check out this infographic.

Case Studies

Once you understand the metrics above, it’s time to start using analytics by:

  • evaluating your acquisition channels with a Lifetime Value(LTV)/Customer Acquisition Cost(CAC) analysis
  • going beyond funnels to paths (path analysis)
  • slicing and segmenting your shoppers according to cohorts
  • predicting potential churn by identifying changes in purchase and retention patterns
  • using actionable insights to react quickly to dynamic business scenarios
  • unifying data from social networks, blogs, ad networks, and billing platforms to make evaluating your performance a snap and day-to-day management a breeze

Completing these types of data analysis can help you uncover your business’s strengths and opportunities for improvement. Below, you will find ideas around implementing customized product recommendations into place, and case studies on how to use data to increase your online store’s revenue.

Product Recommendations

A solid ecommerce strategy is no longer about making decisions off a single data point. You need to use a collection of data to create a 360-degree view of your buyers that can drive upsell, cross-sell and repeat buying behavior. In fact, one of the reasons Amazon continues to dominate is because they use data-driven information to suggest related items and bundles based on what the customer has previously purchased, what they’ve looked at, and what similar shoppers have also purchased.

Ecommerce Analytics will help you track each transaction and interaction to collect insights about your shoppers so you can determine:

By better understanding your visitors’ behavior, you can make smarter decisions to grow your business and build deeper relationships with your customers.

Decreasing Abandoned Carts

One way of decreasing abandoned carts is by reviewing the abandoned carts section of the Store Overview. This area will show you which products generate the most abandoned carts and the most abandoned revenue. This data is telling you that there are a set of products that for whatever reason, customers are not buying.

If you see the same products show up in the top abandoned products week over week, you can then decide whether you want to promote those products in a different way. You might want to change the product image, or how you describe those products. Also, you may want to create a target campaign to push those products, since you most likely have a lot of inventory on those products.

Optimizing Marketing Campaigns

The Marketing Report provides a clear breakdown on how all of your marketing channels are performing by revenue, conversion rate, and the average order value. You may find that there are channels in your business that have very high conversion rates, but the average order value is low. There may be other channels that have a lower conversion rate, but the average order value from those types of customers is higher. What that means is that you might be finding different types of customers in each of your marketing channels.

If you have a high average order value from your Facebook customers, then you might want to increase your spend there to increase a higher value customer. If you have a low order value customer coming from channels like Adwords, you may want to decrease the amount you spend on each new customer you acquire from Adwords because the ROI will be different.

Tactical Ideas

Here are several ideas to help you generate a return on investment with the data you have available via your Ecommerce Analytics suite.

Here is an example of how you can encourage full price purchasers:

  • Data: Pinpoint your best full-price customers, i.e. those customers that buy often without discount incentive.
  • Action: Gather their emails addresses, days since last purchase, order number and lifetime spend. Then, determine how many of your repeat customers are full-price customers.
  • Tactic: Send timed loyalty emails showing them new products before other customers (without discounts) or set up special programs for these extremely loyal consumers, encouraging word-of-mouth promotion that will help you pull in look-alike consumers. In all, increase customer lifetime value for the highest loyal spenders.

Here is an example of how you can launch win-back campaigns:

  • Data: Pinpoint inactive customers, i.e. those customers with higher than average lifetime spend, but who haven’t purchased in a while.
  • Action: Gather customer emails, days since last purchase, order number and lifetime spend. Determine how many of your customers are inactive and find common characteristics between these customers.
  • Tactic: Set up nurture flow emails, offer discounts or incentives to reactivate those inactive customers. In all, you will likely increase click-through rates and repeat customer purchases.

Here is an example of how you can use offers to increase conversion rate:

  • Data: Pinpoint customers with low average order value (AOV), i.e. those customers that purchase based on discount.
  • Action: Gather customer emails, days since last purchase, order number and AOV. Determine how many of your customers, percentage-wise, are discount driven buyers.
  • Tactic: Send discount emails and loyalty program information to these customers on a more regular basis to increase number of orders while maintaining average order value. Also, encourage customers to spread word-of-mouth promotion via discounts for sharing the site with friends. In other words, give them offers to save more as they buy more.

Advanced Options

BigCommerce Insights is a premium report that automatically analyzes store data and delivers valuable, actionable advice. This report has helped BigCommerce merchants increase revenue by up to 25% within the first three months of using it.

Insights provides merchants the ability to drill down on information such as what products should get top placement on your site, and which marketing channels bring you customers that spend the most over the lifetime of their relationship with your brand. Insights includes a number of features that enables online store owners to analyze data in mere moments by viewing pre-formatted, intuitive depictions of your data. In a few clicks, users can view information on repeat purchase rates, cohort performance, and product performance without having to sift through data, create reports, deal with Excel, or any cloud-based reporting solutions.

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