Getting started with Marketing Analytics

You will learn

Learn about Klaviyo’s Marketing Analytics product. Marketing Analytics provides actionable customer and product insights that enable you to enrich your marketing strategy with additional data and use cases for better personalization. 

Before you begin 

Marketing Analytics is separate from Klaviyo’s email and profile plans, and you must have both to access the functionality. Head to our billing guide to learn more about this plan or get started if you are a new customer.

What is Marketing Analytics?

Marketing Analytics is an add-on product to Klaviyo that provides you with actionable customer and product insights to power smarter marketing. While Klaviyo already includes robust performance reporting, the additional insights you can gain from Marketing Analytics enable you to better drive retention, revenue, and relationships at scale. 

Purchasing Marketing Analytics 

New Klaviyo customers

If you are a new customer, you can purchase Marketing Analytics alongside an email plan. 

Existing Klaviyo customers

To purchase Marketing Analytics: 

1. Navigate to your account in the bottom left corner and select Billing.
2. On the Create your plan tab select Current plan to proceed to checkout, where you'll see the option to add Marketing Analytics to your current plan. 
3. Select Marketing Analytics on the checkout page and enter the number of profiles you need for your plan. 

Billing

Marketing Analytics is not included in Klaviyo’s base email and profiles plan, and a subscription is required to access the associated functionality. 

Marketing Analytics is priced based on your active profile count, starting at $100 per month for up to 13,500 active profiles.

Learn more about how Klaviyo bills for Marketing Analytics.

Interface

You can find Marketing Analytics in Klaviyo’s left-hand navigation menu.  

Within the Marketing Analytics item, you’ll see the following tabs to access the associated features. 

• Customer insights
• Catalog insights
• Predictive models

Marketing Analytics feature set

Funnel analysis report

The funnel analysis report provides the ability to see where customers may be dropping off in their journey with your brand. The report allows you to set up and analyze the specific steps of a customer’s marketing journey and the number of customers who reach each step. 

For example, you may create an analysis that starts with customers who Placed Order, then Fulfilled Order, and finally Refunded Order, as shown below. 

Within this analysis, you can review a breakdown of the number and percentage of customers who reached each step and see where you can optimize your marketing efforts.

Conversion overview 

The conversion overview dashboard enables you to analyze your total conversions and revenue, including Klaviyo attributed values. You can also review how many profiles are completing different numbers of conversions and the total revenue they represent. This dashboard enables you to optimize marketing efforts and increase conversion rates by targeting specific segments based on conversion behaviors.  

RFM analysis report

The recency, frequency, and monetary values (RFM) report provides deep customer insights based on purchasing behaviors and automatically categorizes these behaviors and customers into groupings (e.g. Loyal customers). 

These groupings enable you to analyze customer behavioral patterns over time and identify areas where you can optimize your marketing strategies. 

For those customers who may be at risk, you can also use these insights to drive winback campaigns and reduce churn.

Audience performance summary report

By assessing the performance of your individual segments, the audience performance report lets you quickly spot segments that are performing successfully and unsuccessfully. The report provides detailed information on:

• Each of your segments
• Their overall success per channel
• Their total conversions or revenue
  
  

From here, you can use these insights to tailor marketing efforts toward underperforming segments. Examples of some of this report’s features are shown below.

Cohort analysis

The cohort analysis allows you to take a group of profiles with common characteristics (i.e., a cohort) and analyze their behavior over time. This allows you to identify trends and patterns in engagement, conversions, and other key metrics across their lifecycle.

Some examples of customer behaviors you can track with a cohort report include: 

• Repeat purchase behavior
• Customer retention 
• Purchasing behavior after subscribing 

Catalog insights

The product analysis dashboard allows you better understand customer behaviors related to specific product purchases, and craft marketing to match these pathways. 

You can review insights around how, what, and when products in your catalog are driving orders, and align products at the right time in the customer journey.

Some methods you can strategically use product analysis insights include: 

• Adjust post-purchase flow timing
  Set up a flow triggered off of a purchase event and add a wait step based on insights from the Repeat purchase timing card.
• Adjust post-purchase flow content
  Set up a flow triggered off of a purchase event to promote a product recommendation from insights in the Products bought in the next order card.
• Automate recommended bundles/co-purchases
  Set up a flow triggered off of an abandoned cart event with a reminder to purchase and a product recommendation from Products bought in the same cart card.
• Inform your merchandising strategy
  Identify the best products to promote together or in succession in campaigns based on Products bought in the next order or Products bought in same cart cards.

Additionally, the product analysis dashboard creates 2 predictive profile properties in the Predictive Analytics section of a profile. These properties are: 

• Best cross-sell date
  The product analysis report determines the best timing to attempt to cross-sell to profiles. The Best cross-sell date property requires customers to have made at least 1 purchase, and is based on the purchasing patterns of similar customers that have bought the same item. This is a dynamic property that updates daily, but only when a profile makes a purchase.
• Next best product
  The product analysis report also determines the next best product for profiles based on their last purchase. As a profile continues to place orders, this property will automatically update accordingly. The Next best product automatically excludes unavailable items, as well as the first 48 hours of repeat purchase data for a profile. The first 48 hours after a purchase generally has the highest volume of returns and exchanges. Excluding data captured during this timeframe prevents the Next best product property from being skewed.
  
  You can take advantage of this profile property in email sends through the Next best product block. This product block will dynamically show each recipient the next best product they are most likely to purchase based on their last purchase.

Customizable CLV report

The customer lifetime value (CLV) report predicts your customers’ expected purchases and behaviors over time. This report details your customers' current buying habits across each of your marketing channels and functions (campaigns, flows, forms, and segments), and then models potential future purchases based on this data. 

These insights provide opportunities for you to cross-sell and up-sell upcoming purchases, as well as how to best personalize the customer buying experience, including around key times of year and events that matter to certain customers. Examples of some of this report’s features are shown below.

Other benefits 

Custom metrics 

While custom metrics are available on all Klaviyo accounts, purchasing Advanced KDP increases the number of custom metrics permitted on your account from 1 to 50. 

The custom metrics feature in Klaviyo allows you to configure your own events for more accurate reporting and events that better represent your business operations.

By default, Klaviyo provides metrics that track your business’s performance and measure success (e.g., a Placed Order event). However, there may be instances where you need to create custom metrics to more accurately capture how your business runs. For example, your Placed Order events include recurring subscriptions by default, and you’d like to review only orders placed through your ecommerce website.

Some example of common use cases for custom metrics include:

Separating retail and ecommerce events (Shopify or other custom integrations)
With Shopify and some custom integrations, physical retail (POS) and e-commerce orders will come through as a single event (e.g., Shopify Placed Order event).

However, if you would like to separate these out to see the efficacy of each individual event type, you can set up a custom metric like the example below. Here, the point of sale (POS) is not being included in the Placed Order event and combined with other ecommerce data.

Removing recurring subscription events with Shopify, WooCommerce, or BigCommerce
As noted above, standard Shopify integrations, WooCommerce, and BigCommerce will include subscriptions in Placed Order events automatically. This means that they are calculating both ecommerce and subscription orders together. In the example below, by using does not equal, you can isolate and review Placed Order metrics that do not include subscription orders.

Additional resources

Getting started with Advanced KDP

Understanding how Klaviyo billing works