Every brand works towards the goal of customer retention, especially retaining first-time users is a predominant task that requires a lot of user data analysis. If you want your brand to be successful in the competitive market, you will need more data, especially the right tools that interpret the data and drive towards actionable innovation. Let us see about Product Analytics Vs Marketing Analytics.
When we talk about analytics, most marketers are stuck between the choice of Marketing Analytics and Product Analytics. Are they different? Which analytics would be highly suitable for your business?
Let’s explore more on its differences in this blog post
Product analytics helps in understanding critical information such as the number of users signed up and finished the desired action that was intended to happen. In short, product analytics offers valuable insights into the user experience, product usage, and various other aspects. It also helps in understanding user decisions to come up with a better strategy to improve the product.
Marketing Analytics, on the other hand supports you in creating specific marketing campaigns for the customers based on their demographics such as age, name, and location. The marketing analytics tools like Facebook, Google Analytics, and Adobe analytics help you in monitoring your marketing campaigns and supports in making a better choice of investment in the future.
Here are some of the ways how product analytics can bring in the change:
1. With the help of product analytics, companies can understand their user journey and offer a better user experience. Furthermore, the analytics also help in observing all the actions of the user on their website.
2. By incorporating the product onboarding funnel, lets you track certain important user metrics such as from the moment the user started to learn your products till the moment they turned out to be your customer. Additionally, it also helps in identifying the users that got stuck in the onboarding process.
3. The analytics also provide a better understanding of the users on how they interact with your app or product
4. Offers valuable insights on how the data can be used to improve your product and shape it in a better way. These data can play a vital role in making a critical decision about your investment in the future
At the same time, the analytics can work well only if the organization has a certain measure of data, as it is not advisable to come to a conclusion with a minimum set of data. In the case of minimum customer base, collecting feedbacks and conducting a short survey can help you with valuable information to identify the gaps in your product
Product Analytics features analytics segmentation, funnels, and cohorts analysis
1. Analytics segmentation:
Analytics Segmentation supports in offering better insights on the particular events and enables you to choose certain properties that matter a lot. It also offers a detailed demographics of separate events that are usually displayed as charts (line, bar, pie)
2. Cohorts analysis:
Instead of considering all customers are one unit, cohort analysis segregates into similar groups called cohorts which is a subsection of behavioral analytics. It considers different events and enables you to set up activities along with the customer properties, one at the beginning and the other as a goal. It allows you to get more insights such as the required days for users to complete their second activity and give you simplified information in charts which usually segregates the data as the first time, recurring, and power users.
3. Analytics funnels:
Analytics funnels are created to give a better understanding of your customer journey. In general, they are a series of events that you would like your customers to check upon. It helps in identifying the users who are stuck up in the middle, completed the final step, or dropped. By tracking these critical insights like customer dropping rate at every step, you can easily identify the reason behind the drop and bring up the desired change.
Google Analytics is one of the key marketing analytics solutions. It’s popular with a lot of companies that make use of it to track performance. This can further be split into three different categories.
Google Analytics: Google Analytics is one of the standards and free versions that most of the businesses and marketers are aware of.
Google Analytics 360: It is a paid version that offers more advanced features and options like Campaign Manager, integrations with Display & Video 360, removal of sampling, and Bigquery integration.
Firebase: Google’s solution is dedicated to app tracking.
Irrespective of the product offering, both the analytics tools are designed to offer required insights to the marketers who are helping to drive the required outcome. The main objective of the marketers is to optimize the traffic stream, adapt their marketing efforts, budget, and actions towards the source that drives maximum outcome which is also known as attribution.
As mentioned in the above, Google Analytics mainly focus on acquisition and traffic sources and behavior information which centers around generic metrics like sessions, bounce rate, and average session and duration
Google analytics offers very informative reporting on marketing KPIs like the number of views, time on site, completion of transactions, or goals.
Product Analytics Solutions
Product analytics solutions offer insights on how the users are behaving and responding to your apps or websites. They answer some common questions like:
– Why do some customers convert while others don’t?
– What is the top driving factor of user retention and engagement?
– Did the new change of feature cause any desired change in user behavior?
– Who are your potential users and how do their activities differ from others?
– Is there any difference in the retention by the user cohort? Is there a low or high change when users engage with a particular feature?
– All the above questions are difficult for Google Analytics to handle because it offers just the granular level of measurement.
Google Analytics deals with the anonymized traffic data while the latter uses an event-based tracking model designed to track certain actions customers take within a product.
Product analytics tools are intended to collect all of these properties and events link them to an individual user ID, offering insights on how each app or web user is behaving through the customer journey
Both Marketing Analytics and Product Analytics have a place of their own and must be used in conjunction. In short, both the tools possess a symbiotic relationship, when teamed with appropriate tools, they can create a cycle of positive growth for the whole organization.