Kitewheel Executive Interview
Mark Smith, President, Kitewheel
There are many companies in the Customer Journey Mapping
Software space. What makes Kitewheel
That’s a great question. Many customer journey players have
been focused on either journey mapping, journey analytics, or have recently
layered journey functionality on top of existing channel management software,
but it’s not a core focus. At Kitewheel, we provide a single platform for all
of the journey management process: analytics, mapping, and our real pride -
customer journey orchestration. With our platform, our clients can actually
translate that customer journey map into customer actions, in real time. We
help our clients not only use integrated journey analytics to understand
consumer behavior but also make strategic, data-backed changes and get powerful
results. We also stand out as an innovative, team-oriented business made up of
industry veterans who helped establish the discipline.
Customers use many channels.
How does Kitewheel tie together data from disparate channels for a
single customer view?
Absolutely, and it’s so important to understand which
channel each customer is coming from in order to meet them where they are and
create the strongest engagement. At the same time, in order to better
understand each customer, we need to bring together different channel data so
that we can understand the complete journey and not just measure satisfaction
at individual touchpoints.
With our real-time software, we can connect to all channels
and use Kitewheel’s Identity Resolution capability to match and link individual
customers’ behavior from channel to channel in order to better understand their
individual journey and avoid giving the customer repetitive information along
the way. That way we can understand not only who is unhappy and when, but also
unlock insights on why.
Does Kitewheel have the ability, through analytics, to
predict what a customer’s next steps in their journey will be?
We can absolutely predict the most likely path for a given
individual when we examine their experience with journey analytics, but it's
actually because they are a living person that we need to dynamically orchestrate
the journey for them. For instance, we can better understand why a customer
takes a path we don’t expect, and we can correct a path that doesn’t give them
the ideal experience.
From there, we can use a look-alike model or plug into
machine learning and AI tools like IBM Watson to predict what the individual
will do next. Alternatively, we use our array of 20 or so different analytic
and visualization tools to map out what customers’ next steps will be based on
their past actions. This is where we close the loop between analytics and
orchestration – and we do all of this in real-time.
Done right, you could see someone is on a path of
frustration and get them on the right track to a seamless, enjoyable
Customer data is often collected but rarely shared back to
the customer. What are your thoughts on
customer transparency – letting the customer know exactly what is being saved?
There are tremendous advantages to brands being completely
transparent about their use of customer data and even allowing customers to
personalize what data is being shared. In fact, a recent Gartner report
found that putting data visibility and control back into the hands of customers
built more meaningful consumer-brand relationships, improved data accuracy,
limited wasted marketing spend, and boosted revenue. It’s a two-way street:
when a brand trusts a customer to decide their own preferences, the customer
can, in turn, better trust the brand.
Beyond trust, customers are shown to be willing to provide
certain nuggets of data when they know it will personalize their online
experience and grant them greater convenience. Of course, this allows customers
to self-correct when the data is not completely accurate, which also gives the
brand deeper insights into individual shoppers. On the flip side, customer
relationships can quickly sour if they find their data is being mined without
clear-cut results and an efficient, tailored experience.
How does collecting the ‘right’ amount of data build
The "right" amount of data is however much you
need to give you a clear view of the customer experience and determine the best
next step - most businesses get started with data from two or three channels
and build out journey approaches from that starting point. It is absolutely not
a requirement to have a complete view of all customer data in order to get
started with customer journeys. It's also
not just about having data; it's about knowing what to do with it. You can know
every single thing about a person, from hair color to ice cream preference...
but those data points won’t help if you’re trying to sell shoes, for example.
report found that CX has actually surpassed product quality and price as
the most important differentiator for customer satisfaction. That said, showing
customers that you know them matters more than having loads of random data.
With high quality, contextual data, brands can foster a deeper connection with
customers and create a customer experience that is both branded and intimate.
Can you share a case study where providing data transparency
helped increase loyalty for one of your customers?
We recommend revealing data through the experience provided.
For example, we helped Nestlé Gerber create a service to guide mothers and
caretakers through the stages of development of their child, offering relevant
products along the way. For that campaign, we leveraged deep insights into the
customers (e.g. exact age of the baby, if they get diaper rash, if they have
colic) to completely personalize the experience. In that case, the customer could
clearly see the information our client had on them but responded positively
because the information was used to provide helpful guidance and support. Thanks to Gerber’s engagement program and
two-year new parent journey, the company measured a sales increase of 27% for
There is also an interesting flip side to this story, which
shows the potential sensitivity around use of customer data. There were certain
types of data requested from young parents that they didn’t like to share, for
example a new mother’s weight. Although requested for good reason, to assess
progress with feeding, this request clearly crossed a line for many customers,
and their journey would drop off at this point. Kitewheel’s analytics
identified this issue and allowed an immediate resolution (changing the
question/data request); this immediately delivered those customers back onto
their successful journey.
Even if it’s not conventional, brands should put the
customer journey under the microscope and implement changes that make it clear
they are well intentioned and doing everything they can to support the
customer, especially during a time when consumers are increasingly questioning