In today’s data-driven world, businesses need to have a good understanding of their customers and how they interact with their products and services. To be successful, companies need advanced data that provides a complete picture of product and marketing innovations.
As many companies move toward digital transformation, marketing and product teams must work closely together to achieve common company goals. In addition to product-specific analytics that help identify why certain metrics are falling, some organizations these days are already using marketing analytics to “growth fractureto identify effective marketing campaigns and engage customers over time.
Understanding marketing and product analytics data serve different purposes and can be combined to drive business growth; it is necessary to identify and have an appropriate combined strategy.
Differences between product analysis and marketing analysis
1. How does product analysis work?
Product analysis is the process of collecting and analyzing data about the customer journey and how they interact with products through built-in tools. From this, companies can understand the real thoughts of users, identify patterns and trends, and make data-driven decisions to improve products.
Using product analytics tools like Mixpanel or Amplitude, you can collect data from various sources like mobile apps and other digital channels to answer questions like:
- How often do customers use the product? What features do they use the most?
- How are your potential users? And how does their behavior differ from other users?
- Are there any pain points or areas that could improve the user experience?
- What are the key drivers of user engagement and retention?
With a powerful segmentation engine, user group trends, and in-depth analysis of user behavior, product analytics software provides advanced data that can be time-consuming to collect and analyze to help you make product improvements or additions. without effort.
Read more. Top 5 Best Product Analysis Tools of 2023
2. How does marketing analytics work?
Marketing analytics, on the other hand, is the practice of using data related to a company’s marketing activities to evaluate the effectiveness of a company’s marketing efforts, identify areas for improvement, and make data-driven decisions to optimize future campaigns.
Marketing analytics typically involves using tools such as Google Analytics (GA), Adobe Analytics, or HubSpot to collect data from a variety of sources, such as email campaigns, social media, paid advertising, and other marketing channels. The software can be used to answer questions such as:
- How many leads or sales did a particular marketing campaign generate?
- Which channels drive the most traffic or conversions?
- What is the return on investment (ROI) for each marketing campaign?
- How do customers respond to different messages or offers?
Among all, GA is undoubtedly the king of marketing analytics solutions and is designed to understand the first part of the user journey: traffic source, page views, time on site, etc.
3. How does Google Analytics 4 (GA4) change the concept?
With the introduction of Google Analytics 4, the technology gap between marketing analytics and product analytics has narrowed significantly.
As a significant update to Google’s popular analytics platform, it focuses on event-based tracking rather than page-based tracking. In the past, Google Analytics tracked website interactions based on page views. With GA4, events such as clicks, video views, and other interactions are tracked instead. This change allows businesses to more accurately track user interactions, giving them a better understanding of how users engage with their website or app.
GA4 also introduces new reports that focus on customer lifecycle analysis, giving businesses a more complete view of the user journey. These reports include metrics such as user engagement, user retention, and lifetime value, giving businesses a better understanding of how users interact with their products over time.
How to combine product analysis with marketing analysis?
By combining marketing and product analytics, you can gain rich behavioral data that helps you reach the next wave of users, drive digital product innovation, and deliver a customized experience. Here are some tips to make it relevant:
1. Provide a seamless user experience
At first, you may only have partial visibility into the user journey. Blind spots caused by disconnected data and missing information put you at risk of losing potential users down the road. Gaining a holistic view of the customer experience, from acquisition to engagement and retention, is critical to developing a compelling digital product and marketing plan that delivers real value to your consumers.
Marketing attribution data gives you a comprehensive picture of users before they even download your app. It often begins with:
- Gaining knowledge about the complete conversion process. knowing where customers came from and how they got there can provide important, upfront information about the users interacting with your app.
- Understanding which touchpoint they would like to perform immediately after entering the app can serve as an indicator of what they expect to see first.
- Knowing which channels, campaigns, ad sets, and creatives can drive the most valuable customers to your app (usually based on LTV and ROAS metrics).
After users log in to the product, in-app event analytics provides them with information about their engagement rate and LTV. By combining this marketing analytics data with product analytics, you can see how customers interact with your digital products (eg, which features are most preferred, customers’ last five purchases, their next twenty predictions, etc.).
2. Understand customer needs
Imagine how you, as a customer, would want the brand to connect with you and what the ideal user experience would look like. This will often require incremental marketers and product managers to deliver personalized journeys for individual personas based on attribution data and then apply appropriate engagement techniques to increase conversions.
By integrating product and marketing analytics data, you can identify user segments that are most engaged with your products and marketing activities. You can then run a marketing campaign to send personalized messages to users, suggesting their preferences. For example, if a user has spent a lot of time searching for a shirt in a retail app, businesses can send them an email with a personalized offer or recommendation related to that product.
3. Know user removal points
Dealing with your customer attrition and identifying where you are starting to lose prospective customers is critical to the growth of your mobile app. As a growth manager, you need to track attribution data; know what’s driving churn, recognize where users are and what metrics are affected.
To optimize user experience, increase engagement with new features, and retain users over time, you need to measure end-to-end engagement levels for key in-app events. Sometimes even a small change to a seemingly minor feature can completely change the way consumers interact with your app.
4. Head in the right direction first
Time is of the essence for every project. Running large-scale marketing campaigns will save you a lot of time and money if you can shorten the time between starting a campaign and getting actionable insights into user LTV.
Innovative marketing analytics tools that apply sophisticated machine learning technology can predict long-term performance within just one day of a consumer installing an app. This facilitates faster decisions about where to allocate marketing resources for maximum return on investment (ROI).
Furthermore, you can personalize your marketing and communication strategy depending on deep digital product intelligence and predictive analytics models that evaluate previous user actions.
This means that you need to create customized in-app notifications or messages for different user segments based on their propensity to convert for your customers than ever before.
Let’s combine Google Analytics with Mixpanel.
Clearly, marketing analytics and product analytics live in a symbiotic relationship and cannot replace each other. When both product and marketing teams are equipped with the right tools, it creates a sustainable positive growth cycle for the entire corporation.
Marketing can use GA to optimize marketing campaigns to acquire new users, giving product teams a larger user base to identify new ways to improve engagement, conversion and retention. Organizations can then identify potential users by applying Mix kill and making them lawyers. Likewise, they can identify users who are most likely to churn and offer different marketing and product experiences to reduce churn.
Since many organizations are using GA extensively these days, integrating it with a product analytics tool like Mixpanel can help increase customer knowledge and improve their experience.