Products function in an extremely competitive landscape vying for every impression it can get among the millions of potential customers available online. Getting your startup visible or discoverable is one thing, getting them to convert on your website and retain them is an even tougher task with the plethora of services and products that the consumer is forced upon. This is why it becomes so very important for products to understand each and every activity of the user right from the first time a potential customer/ user discovers their service or product on the web to the point they convert and start coming back to their website.
There are plenty of data that’s available to internet products these days and a vast variety of analytic tools to analyze them as well. A few years back, one would have managed analytics and data tracking using just a Visitor analytics tool like Google Analytics, but that is no more the case now. With growing competition, you have far less room to fail. Based on your website and your requirements you can choose from the various Analytic Tools that’s available to you. More often than not, you would need to have a combination of these tools below to better understand user behavior. The below chart gives you the various classes of Analytic tools and their strength in measuring various parameters:
It is crucial for a marketer to appreciate the insights data can provide on user behavior and take necessary actions to correct and optimize wherever required. It is also crucial for a marketer to measure the right data and understand it’s essence for better improvement of the customer lifecycle on their website.
In my previous post, we had discussed the importance of measuring the right macro metrics. For understanding and validating Product/ Market fit, one needs to measure Activation and Retention. However to completely understand the lifecycle of the Customer one needs to also measure the other three elements: Acquisition, Revenue and Referral.
Funnels are a great way to understand user behavior on your website. They are visual, simple and map well to most of the events related to measuring the macro metrics. But Funnels alone have their limitations as well. Imagine if you wanted to measure the impact of repeated product iterations you have pushed out to during a period on the revenue. It becomes extremely difficult to track the same using only funnel, one because the impact on revenue is a long term thing and also because you would need to segment users who signed up during the period when each iteration was rolled out to effectively understand the impact on revenue for the set of users who started off with a particular variation of the product. This is where cohorts play an important part. Think, I would cover cohorts in the next post and explain in detail the methodology to track metrics like retention, revenue, impact of feature iterations on both and more. In this post, we will focus on using Google Analytics in tracking the channels resulting in any of your user interacting with your brand, converting on your product/ service and also on coming back to your product/ service. The Digital Marketing Funnel as represented in the figure earlier can be broken down in to 3 components:
- TOF – Top of Funnel
- MOF – Middle of Funnel
- BOF – Bottom of Funnel
Top of Funnel:
Top of the funnel represents the first interaction a user has with your brand/ product. There are plenty of channels on which the interaction would happen and one would need to optimize for each of the channels the interaction happens on. The best solution is to always focus on at max two of the channels where the interactions seem to be most effective. With the new Universal Google Analytics Tool, you can get the channel details at Acquisition » All Traffic.
The above table gives you a good understanding of all the various channels that drive traffic on to your platform. You can export the data to an excel sheet and then use a pivot table to understand what medium acts as the best option to drive first time traffic so that you can focus and optimize for that channel/ medium.
You can drill down further to understand the best referral sources through Acquisition » All Referrals
Determining which sites have referred the best traffic to your website is important as it enables you to focus on those channels. You can focus on important parameters like Bounce Rate and Time Spent on site to understand the engagement of the users coming from various channels. Not only that, you can also identify websites that are similar to the ones driving traffic on to your website by doing a search on Google [ Use the search query related:”site name”]or on Similar Web to try and leverage on to the similar audience on those sites to generate traffic. For eg: If weheartit.com is a major referrer to your site, then doing a search for related websites on google gives you these results:
The above search result gives you a healthy number of similar sites with similar target audience who would be interested in your site. Refining and cross-posting your contents across these websites can also help you in getting additional traffic. You can even automate a few of these by using a service like IFTTT where you create recipes for simultaneously posting on a number of these platforms.
Remember, it’s always a good practice to tag the various URLs you use to drive traffic from various campaigns on referring sites. You can use the standard URL builder which google provides to generate tags.
By generating campaign URLs, you can identify the source of referrals to your website, whether visitors found the link from within a newsletter, social media post or other marketing campaigns. By naming the three main campaign tagging elements: source, medium and campaign, Google Analytics will display information about where the referral originated. Simply complete the tool’s three-step form.
Here are just a few examples of valuable KPI data points you might consider tracking as part of acquisition:
- Organic Search (SEO)
- Paid Search Marketing (SEM)
- Social Campaigns
- Banner Campaigns
- Links from External Sites
- Links from Online Videos
- Email Recipients
- RSS Subscribers
Another important parameter which you would want to track is the landing page and how you can optimize them for better conversions. Google analytics helps you identify the most important landing pages on your site and the user flow thereafter. This would give you a better understanding on which pages are performing badly and helps you understand what you can do to further improve user interaction on those pages. [Behavior » Site Content » Landing Pages or Content Drill Down ]
On Improving weak landing pages:
- Optimize the content to make it relevant if it’s outdated.
- If it’s your main landing page, change the message or positioning if required. Use the heatmap tool to better understand the user interaction on the pages and optimize your page accordingly.
- Make the content more comprehensive so that more people will find it interesting and informative.
- Build more relevant internal links to the weaker pages to give them more link juice.
- You can prompt the user to sign-up for email newsletters or at least try and convert them on any of your micro-conversions before the user leaves.
Middle of Funnel:
Middle of Funnel in the Digital Marketing Funnel is the point where in the user is moving from an initial product or brand interaction to a first sale/ to any major interaction on the platform. You might not be able to get a user to convert during this stage but it’s crucially important for companies to target micro-conversions during this stage.
It’s important to track the sources or channels through which the users come back to your site during this stage and it’s also important to measure the paths taken by the users in completing the micro-conversions or goals set on your page. For understanding user paths, GA has an option called Visitor Flow under Audience that visually represents the user path on the website and the drop-offs at each stage. The Visit Flow Report is a nice and a better representation of the traditional click path report. One can view the visitors moving between nodes. One also has the option to view particular segments of users based on region, campaign, traffic source, country etc and their flow/ browsing pattern on the website.
You can also create your own funnel for any of the goals you have set using GA to better understand where the users are dropping off. For setting up goals or micro-conversions in your site, you would need to clearly define the business objectives for creating goals (micro-conversions). Few examples of good engagement goals to track:
- Account signup
- Email signup
- RSS subscription
- Watching video
- Content interactions (e.g. photo zoom, faceted search attributes, etc.)
- Product Purchase
The goals would vary based on the type of website you are measuring for. To set up these goals, you can login in to the admin panel of your Google Analytics dashboard and then click on the Goal tab.
You have different goal types to chose from: Destination, Duration, Pages/ Screens per visit or Event. In case of an E-commerece website for eg, if the marketer needs to track how many users complete the check-out process, then he/ she would have to chose the type of the goal as “Destination” in the first step. In the second step he/ she would have to define the destination page which would complete the goal (Conversions).
For creating the funnel, you would need to specify each step (page) the user traverses before completing the final goal. The funnel visually represents each stage in the micro-conversion process also specifying the drop-offs at each stage. You can create, based on your requirements, multiple mini-conversions and funnels to better understand user flow during this middle stage of user lifecycle.
[Fig: A funnel representation of a goal set to White paper Downloads from the start page clearly indicating the conversions and drop-offs at each stage.]
In the middle of the funnel (MOF) for the Digital Marketing Funnel, it’s also important to analyze the most effective and popular channels that bring the user back. For this, GA provides Multi-Channel attribution tools under the “Conversions” section. There are various attribution models one could use. For a full guide refer this. The Linear Attribution Mode, which gives equal weightage to any channel in the funnel irrespective of where it appears, gives us great insight in to which channel accounts for the most revenue overall. You can use the Model Comparison Tool in GA to find this out:
For figuring out the most popular channels in the MOF, we would have to do some manipulation using excel to weed out the first and the last interaction channels.
Bottom of the Funnel:
The bottom of the funnel is the last touch before someone buys. These channels are very important as it let’s you identify which channels to focus on to complete conversions. You can find this data in Conversion > Attribution > Model Comparison Tool and select your model as the Last interaction.
You can use these data on the best channels for driving traffic on to your website to further improve and optimize.
In addition to standard segments that are available in GA to chose from ( You would have noticed this when we discussed the User Flow path), there are also a wide variety of custom user segmenting options that lets you better understand each set of users. You can create your own segments from the dashboard by clicking on the drop-down next to the All Visits tab that’s present as default. GA with the latest update now has the ability to segment visitors and not just visits, which is something GA lacked compared to tools like Kissmetrics and Mixpanel.
Now click on the Create Segments Icon to define your segments. There are a wide variety of parameters you can use to create segments or else you can use any of your own created events as well to define a segment.
Refer this post for a great list of custom advanced segments which you can use.
Using segments, you can slice and dice your audience in ways never imagined before. You can create segments based on first purchase value, browser being used, platform being used, device on which the visitor opened the site, purchase value during a period etc. I can very well use this data to do a cohort analysis which is very important at an early stage especially if you are on a lean methodology and constantly iterating, measuring the behavior of the set of users who come in during each of these iterations. Even otherwise, there is tremendous amount of insights analyzing segments will give you.