Three ways to create insights from consumers' click histories
Without
any action behind it, data is just a bunch of numbers. Clickstream data
is particularly valuable, providing insights about what consumers are
doing.
Without
any action behind it, data is just a bunch of numbers. Clickstream data
is particularly valuable, providing insights about what consumers are
doing.
Data alone does not lead to insights. Analyzed data backed by a hypothesis and placed in the right context, on the other hand, does.
Marketers
often fail to use their data to create actionable insights – that is,
insights that are clear and relevant to their businesses – to better
understand and connect with customers.
Instead,
they are viewing data as simple numbers, forgetting to turn it into
actionable steps. According to Forrester research from earlier this
year, only 29 percent of companies successfully extract actionable
insights from the data they collect.
The difference between data and insights is as blatant as the difference between a fake connection and a genuine human interaction,
and it can play a big role in customer interactions. Clickstream
information is a particularly good set of data for marketers to examine
if they want to understand their customers better and connect with them
based on their actions.
The many benefits of clickstream data
It's
common for businesses with web analytics to examine their own customer
flow and navigation path funnel. While this information is useful in
identifying customer segments, optimizing user experience, and
minimizing drop-offs through the conversion funnel, it's like examining
one section of an industry with a magnifying glass: When you pull back
the magnifying glass, you can examine not only how customers are
interacting with your brand, but also what they are doing before and
after they arrive at your site.
Clickstream
information is based on consumers' actual click and browsing behaviors,
with records of click-throughs and URLs visited collected in the order
they occurred, giving marketers important, industrywide insight into
online behavior, the customer journey through the funnel, and user experiences.
Rather
than providing simple numbers of visits or sales, clickstream
information reflects consumer behavior based on their activity and
identifies areas companies could improve where the competition might be
doing it better. Partnering with a third-party allows businesses to
bridge the gap between knowledge of their own sites and knowledge of
other companies in their space.
Listen to what your clickstream data says
The
insights garnered from clickstream data may not always match your
hypothesis, but they are always useful if you ask the right questions.
At Jumpshot, we examined click history to help an airline that was very
interested in understanding its frequent flyers' loyalty so it could
increase its share with infrequent flyers.
The hypothesis was that the airline's frequent flyers must be loyal customers and
should be catered to because of their dedication to the brand.
Infrequent flyers were seen as loyal to other airlines, and efforts
should be made to switch them.
We
compared the clickstream data of three customer groups of the airline
– frequent flyers, infrequent flyers, and those who had never flown with
this airline – to see their flight transaction activity both on this
airline's site and those of its competitors.
The
behavioral group that had been deemed most loyal turned out not to be;
those customers just flew the most overall. They bought competitor
airlines' flights at a higher rate than the general population, too. We
also found that infrequent flyers were not just infrequent with this
company, but were infrequent overall.
Our
insights from the clickstream analysis taught the airline's business
leaders to focus on increasing the rewards program to persuade frequent
flyers to be more loyal to their brand. That could result in a
widespread influence on the airline's marketing messaging, branding,
perks, and even its product growth.
Frequent
flyers offered a bigger pot and opportunity to increase market share
than infrequent flyers, who just didn't fly as much, creating a smaller
pot).
Don't
collect data just because numbers are nice to fall back on. Instead,
focus on collecting information like click history that is directly tied
to your business objectives and key performance indicators. Identify
what you want to learn, and focus your collection and analysis on that
specific data subset.
Make the most of your clickstream data
Creating
actionable insights out of your data is essential to portraying a full
and accurate picture of the customer journey. Maximize the effectiveness
of your clickstream analysis by employing these three tactics:
1. Have a hypothesis
This
is a minimum requirement for a data project to be efficient and lead to
insights. Without a hypothesis, you're just wasting time. The more
specific you are in your data requests, the easier it is for your data
team to pinpoint exactly what they need to pull, analyze, and provide.
You
don't have to be sure of the outcome, and the data may prove you wrong,
but that's OK. Just be sure your data team enters a project focused and
that they reach a conclusion.
Let's say you run a display campaign to drive awareness and clicks to your own site for a product. If you sell that product through third-party distributors,
like Amazon or Target, your hypothesis might be that your display
campaign is influencing purchase behavior and conversions on these
third-party sites. Without clickstream data, it's very hard to connect
those two pieces and prove or disprove this hypothesis.
2. Tie your analysis to KPIs
Your
analysis might reveal plenty of information about how consumers reach
and interact with your brand or with your competition, but not all
information yields actionable insights. You might find that consumers
searching your website tend to search three times. That's interesting,
but you don't gain real insights from it without understanding how their
search activity affects their subsequent behavior or how it differs
from consumer search activity on competitors' sites.
Structuring
your hypothesis and analysis around KPIs diminishes the risk of
reaching insights that are not actionable. If your leading KPI is, say,
trial subscriptions, look into the trial conversion flow of your
competitors, and reverse engineer their customer journey through the
funnel to detect conversion and abandonment trends at each step.
If
the vast majority of consumers bounce during step three of five on your
site (but not on your competitors' sites), test out consolidation steps
to improve the user experience and increase conversions.
3. Identify your output goals
Without
a clear goal for what you intend to do with clickstream data, you
cannot transform it into actionable insights. Are you studying customer
journeys to optimize conversions or user experience? Are you looking for
details about PR or case studies to grow brand awareness and generate
leads?
Answering
these questions and setting intentions for your data will help you in
many ways, from filtering data requests from the get-go to guiding your
thought process when focusing your data request and analysis.
By
analyzing customers' online actions – clicks, purchases on other sites,
and their browsing history — with specific output goals, you reveal a
world of insight into how they interact with your brand's web
properties, your competition, and how they react to your offering.
Don't collect clickstream data just for the sake of collecting it.
Understand what you want to investigate and how you can benefit from
it. Make sure it's relevant to your company, and then analyze
clickstream data to better understand your customers' actions and
optimize their experience.
Marketers
need to go beyond just the numbers and patterns that data provides if
they want to successfully understand and connect with consumers.
Focusing on customer actions will lead to a better understanding of your
audience and what resonates with them, increasing the success of your
marketing efforts and, ultimately, creating a better business.



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