Customers are a difficult breed to please.
Let’s say you’re in a restaurant for a meal. There aren’t enough tables available, so you’re in a long queue outside the restaurant. After waiting for a long time, the staff finally seats you, but in a smoking area when you requested a non-smoking booth. The staff took your order but couldn’t even serve a glass of water for another half an hour.
If you haven’t already walked out of the restaurant, you have incredible patience. Most customers probably wouldn’t share the same level of understanding as you.
Customers drop-off within a journey when they encounter an obstacle. The issue could be anything – from a payment gateway that can't process a customer’s credit card to a web page that takes a few seconds longer to open. Customers expect good and quick service. They aren’t willing to compromise on anything less than perfect.
If a customer’s problem was resolved during their first interaction, 67% of customer churn could be avoided. But issues can crop up at any point within a customer journey. Businesses need to view the entire customer journey as a whole to pinpoint where customers are stuck and what’s hindering them from moving forward.
One way businesses can accurately visualize an entire customer journey in real time is through customer journey analytics.
Customer journey analytics assesses how a customer engages with a business within a customer journey. It provides a comprehensive view of every customer interaction across separate channels that gives insights into a customer’s movement, time spent at a touchpoint, and helps detect pain points from a customer’s point of view.
Today’s businesses are all about customer experience. After cracking the customer service code, businesses realized that enhancing customer experience makes it easier to approach a customer, and subsequently purchase a product or service.
To make a customer’s interaction with an organization as seamless as possible, companies have made ample use of integrations. This has resulted in numerous channels that function as standalone “organs”. These organs are integrated to form parts of a whole customer journey.
All these “organs” accumulate a ton of discrete data that doesn’t necessarily originate from a common source. As a result, the data that an individual customer generates within a customer journey is treated as a siloed entity.
Businesses often find blindspots within a journey since they can’t see large streams of data for certain touchpoints at a time. Data silos are a pressing issue for organizations that lose potential customers in the middle of a journey, not knowing what caused the drop-off.
Customer journeys are already complex without adding cross-channel communication to the mix. Some of the most common issues that businesses need to tackle are:
By adopting an omnichannel approach, businesses now find themselves with many datasets originating from different sources and available in various formats and data types. Data is great and helps marketers truly understand who their customers are and what they want.
Data could come from a host of offline and digital channels. Data from event registrations can be tracked in an event management platform. First-party data in the form of customer feedback surveys, data in a CRM, and social media patterns have made it easier to gauge customer behavior about what they want and what they don't.
However, businesses also need to invest a lot more time and energy to decipher this data and make an informed decision about their customers as most of this data is in silos. Your business won’t be data-driven if you don’t analyze your existing data.
Think of this situation as studying for an exam. You may have all of the textbooks you need for a course, but you’ll never ace the exam unless you actually crack open those books and study.
It becomes difficult to analyze every piece of data that frequently flows your way. And this is only the data that you obtain from one channel or segment of the entire journey. Having to analyze each segment individually becomes cumbersome to say the least.
By the time you have finished analyzing data in the last chunk of a customer journey, you’ll have fresh data at the beginning of the journey. Having all of this data doesn’t mean much unless you can get actionable insights in real time.
Let’s go back to the example that referenced studying for an exam. Ask yourself, “if I wanted to score As in all of my courses, would I study the course material for just one subject or all of the subjects?"
Organizations often prioritize a single touchpoint over the entire journey. It’s easy to make this mistake, especially when dealing with loads of data at each touchpoint.
Data across a journey isn’t equally distributed; some segments accumulate data in a more digestible form, while others may be slightly harder to comprehend.
Case in point: customer onboarding.
The customer onboarding stage is at the very beginning of a customer journey and has the most available data. Because of this, marketers can quickly understand what messaging appealed to potential customers, and what kind of products piqued their interest. This helps marketers create and push customer-oriented advertisements to specific market segments.
However, at other stages, such as checkout, it becomes more difficult to understand why a customer might have dropped off.
Did the customer change their mind or didn’t find the payment option they were looking for? It could be possible that their discount code didn’t work or they faced some technical difficulties in getting their payment processed.
Whether a customer drops-off at the beginning or the end of the journey, at the end of the day, that’s still a customer lost.
Being able to track which touchpoint caused a prospect to become a customer with the help of attribution software, is an immediate goal marketers would like to achieve. In doing so however, businesses get so caught up in trying to visualize one touchpoint that they end up neglecting the journey as a whole.
While it’s necessary to enhance a customer’s experience at each touchpoint, it’s also important to take a step back and see how the entire journey pans out. Focusing all of your attention on just one segment of the journey could leave another segment severely lacking.
Consider a situation where you spend a lot of time reinforcing the windows in your home for added security. However, you forget that your main door doesn’t have a sturdy lock in place. Ultimately, unless you fix that door as well, all of your efforts to make your home risk-free will go in vain.
When a customer interacts with a business, for that small window of time, the customer is in need of something. They’ve gone through the process of exploring a solution and have spent some of their precious time looking at what a business has to offer.
As customers begin their journey with your business, they may encounter a few obstacles during the process. Ideally, you’d eliminate any pain points that your customers might face. In reality, however, you wouldn’t know until you hear about it directly from a customer or analyze the entire journey in advance.
How long do you think a customer will be willing to wait for the problem to be resolved in the process?
If you can’t wait more than a few minutes for your burger order, why do you think a customer would wait just as long for the problem to be resolved?
Time-gaps are the enemy of any process. Nobody appreciates waiting a long time before proceeding further. Customer experience is greatly affected by the length of the turnaround time (TAT).
of adults feel that valuing their time is the most important thing a company can do to provide them with a good online customer experience.Source: GetFeedback
Being able to assess and resolve issues in a timely manner, is an issue most businesses still struggle with today.
How people feel today can be very different from how they’d feel tomorrow. Just because someone is craving a donut today doesn’t mean they’d have the same craving in the future as well.
Behavior-driven engagement elevates customers from cold leads to hot prospects that are willing to be converted into a customer. Customers exhibit similar patterns, but at the end of the day, they’re still human. Data cannot tell you how customers feel and what they want – but it can come pretty close.
It’s easier said than done.
We know that marketers get immense amounts of data. Trying to piece together data that can actually analyze a customer’s behavior and point to a meaningful decision is tough.
This data quickly gets outdated if it isn’t acted upon in time.
Consider an example of someone looking for hotels in Thailand during the summer season. The same person may not search for hotels in Thailand in other seasons. Keeping his historic data will be redundant since he probably won’t fly to Thailand during that period.
Businesses find themselves with so much data that is begging to be consolidated to provide a more vivid picture of the customer in question. Unless a business can understand its customer’s behavior better, the business will never be able to anticipate what a customer might need from it in the future.
Customer journey analytics seems to be quite similar to another process known as customer journey mapping. However, these two processes are quite different from each other.
The most prominent difference between journey analytics and journey mapping lies in the customer. A customer journey map is created before the customer even onboards the journey. It’s designed by the business team, which is mostly considered a ‘Happy Flow’ of how a customer’s journey would pan out.
Even when marketing teams acknowledge possible pain points in their mapping exercise, it’s never a completely realistic customer journey. Customers exhibit different patterns and behavior at different points in the journey.
As much as we’d like to believe that we know our customer really well, the truth is that we’ll never truly know how a particular customer would interact with us during the journey.
Customer journey analytics provides a more comprehensive and real-time view of the customer within the journey. This means that at any time and at any point in the journey, marketing teams can assess hundreds of customer interactions and interpret customer engagements instantly.
Customer journey mapping
Customer journey analytics
Interpretations are more subjective in nature and encapsulate only a small sample set of customer behavior.
Millions of point interactions can be interpreted immediately and in real time.
Not actionable in nature - journey maps provide fewer opportunities for taking action in the middle of a journey.
Highly actionable in nature - with the help of aggregated data, teams can find pain points and trigger responses to mitigate them.
They are more static, and limited to what the business would view as customer behavior. This prevents a business from making point changes across the journey.
They are quite dynamic in nature, and provide actionable information. Data obtained points to a more current view of customers and their behavior.
Customer journey mapping essentially acts as a medium for building a visual narrative of customer experience. Customer journey analytics, on the other hand, optimizes customer experience by analyzing a situation and arriving at a responsive measure for areas of improvement. If journey maps were the script for a movie, customer journey analytics would be the finalized version of the movie after seeing the test audiences' reactions.
If you’re still wondering whether this type of solution should be seriously considered by your team, here are some of the benefits enjoyed by businesses that already employ a customer journey analytics solution:
The biggest benefit of customer journey analytics is monitoring the churn rate within a journey and preventing a potential drop-off.
According to McKinsey, businesses are around 33 percent more likely to predict customer churn and satisfaction with journey analytics. By detecting behavioral indicators, customer journey analytics can essentially spot situations for customer churn and gauge whether a customer is about to drop-out of the process.
Customer experience is more than just heuristic user experience and some auto-fill forms. Customer journey analytics aggregates data from various sources to establish a unique identifier for a specific customer. Every time a customer interacts with the business, their historical data is retrieved to enhance the customer experience.
For example, someone who had a few items in their shopping cart on their previous visit to the website will find those same items waiting for them in the cart on their next visit. Not only does it save a customer‘s time from having to search for those items all over again, but also nudges them to complete the purchase.
Most importantly, customer journey analytics provides the scope for A/B testing journey changes, and seeing if there are any improvements. Customer retail analytics can monitor how a change, either big or small, fared during a real-time customer interaction. By monitoring how a customer responds to this change, businesses can assess the effectiveness of the customer experience exercise.
The end goal of all this is to convert a customer. Analytics helps identify which customers are in the market to buy something, and helps teams focus their energy on those customers. Analytics also provides information about existing customers that could be swayed to make another similar purchase.
For example, if a customer bought a pair of sneakers online, the analytics tool would keep a record of the purchase and would push a pair of socks at the checkout stage as an add-on they might be interested in.
Customer journey analytics is perfect for pushing offers, cross-selling, and building customer loyalty.
Analytics can indicate if a journey is not viable for a majority of customers. By identifying inefficiencies in the journey, you can take steps to optimize the process or replace it with another course of action. Since analytics provides insight on macro and micro-interactions, journey visualization becomes a lot easier. Clogged or inefficient customer touchpoints can be easily spotted a mile away.
Optimized operations help businesses eradicate bottleneck practices and make their business as efficient as ever, while providing a seamless customer experience. Being on top of operational inefficiencies can help businesses better anticipate customer needs since the teams don't have to spend most of their time filling in journey gaps.
With customer journey analytics, businesses can enhance customer interactions and boost engagement. By providing a 360-degree view of the customer journey, customer journey analytics tools help companies adopt a concentrated and customized approach that optimizes the overall customer experience.
The following list contains real user reviews for the top five customer journey analytics software on the market. To qualify for inclusion on the customer journey analytics software list, a product must:
* Below are the five leading customer journey analytics software from G2's Spring 2021 Grid® Report. Some reviews may be edited for clarity.
Insider is a multichannel growth management platform that creates customer segments through data unification. It matches profiles through data from surveys and cross-channel sources, and creates AI-backed segments resulting from predictive modeling tools.
“The support from Insider’s growth team and our strategic account managers is the highlight of our interactions with the platform. The scenarios they provide us with and the real-time support we get when we are creating personalization campaigns have been a life-saver on many occasions. As a result of these, we’ve been able to optimize the overall performance of our website and key metrics across the funnel.”
– Insider Review, Abigail K.
“Sometimes the statistics for certain campaigns we run with cross-channel tools are not available and we need to use a data studio. Which we think is not really much to dislike.”
– Insider Review, Trang T.
SharpSpring is a revenue growth platform that uses branching logic to engage leads at critical points within the journey. It can synchronize information with its in-built CRM suite to set up buyer personas and factor in natural lead decay over time.
“Easy to use interface is combined with robust functionality for sales and marketing. Creating and segmenting lists, customizing everything from lead scores to reports is pretty easy. Life of a Lead is the killer app here. You can see the detailed activity history of each lead, beautifully laid out. Automation is easy to set up and very flexible. The Perfect Audience retargeting system is a great new addition. Team is responsive and knowledgeable. You can have confidence in this system. All at a nice price, too.”
– SharpSpring Review, Andy F.
“Email builder could be more dynamic - there are some static features; spacing, limited text blocks, and alignment, and a few of the issues I've run into with senior management where SharpSpring limits how you can build emails. I think they lack in this field when stacked against other marketing automation platforms, but they have made some additions/corrections to the email builder in the past few months, which brings more faith in the people behind the product - knowing they will deliver on the issues that continue to be brought up - SharpSpring gives each of their partners (whether directs, like us, or agencies) a voice, and I find that really valuable.”
– SharpSpring Review, Sam D.
WebEngage is a customer data platform and marketing automation suite that can monitor live stats across applications, websites and marketing campaigns. It allows users to design funnels to eliminate bottlenecks and identify all the possible drop-off stages within the customer journey to improve user conversions.
“Our company noted the great simplicity that this software has for both customers and us, especially when segmenting customers with respect to their web activity. It also has an excellent data flow aimed at travel with specialized assistance for which the clients make the best decision. In short, by using this software, we had better communication with our customers.”
– WebEngage Review, Heba M.
“There is not really much I dislike about the tool, but of course, there is always room for improvements. The Analysis system can be improved, i.e. data comparison, funnel filters. On-site notifications do not have clear insight, it's not at its best & easy as creating a push notification. Creating a segment takes some time. Maybe this is something to look at.”
– WebEngage Review, Asif K.
NetBase is a market intelligence platform. Its customer analytics tool, NetBase Voice of the Customer, uses artificial intelligence to deliver deep and actionable insights about customer behavior and satisfaction, purchase intent, competitive preferences, and provide an overall NPS reading.
“This is a platform that provides you with an analysis of social networks to drive your company to obtain the best results of the behavior of the audience, points of interest, so you can differentiate nuances and quantify them. You can create a constant workflow in your team and generate a greater experience for potential clients, increase your income and sales, as well as channel your work into what your clients are interested in. Its interface is good and easy to use.”
– NetBase Review, George P.
“There's nothing we dislike on Netbase Quid, but something I'd like to see improved is the demographics data that can mislead depending on the country you are doing your analysis. This is probably because of the source of data Netbase uses to provide Demographics insights that are based on United States sources, which mislead analysis outside the United States.”
– NetBase Review, Guilherme C.
Adobe Campaign is a set of solutions that helps marketing teams personalize and deliver campaigns. Its analytics offerings, known as Adobe Analytics, include multichannel data collection, creating processing rules for real-time customer segmentation, tag management, and data storage.
“Extremely easy tool for visual analytics, email marketing solution, and lead segmentation product with all the productive functions for effective marketing. Adobe Campaign helps create effective process reports which help in tracking campaign results. Adobe Campaign offers the user a power to manipulate advertising processes through different channels and also for simple marketing campaign automation.”
– Adobe Campaign Review, Alex W.
“It's very clunky and old-fashioned and not very user intuitive. It is quite slow when there are a lot of processes happening, and the tool to check how the communication has performed is not the best analysis tool.”
– Adobe Campaign Review, Harsh S.
The biggest crime anyone could commit is not to use the data they already have and to take action based on it. Improving customer experience is an ongoing process and analytics is key to understanding customer satisfaction.
Customers need to be understood well. They love seeing affirmative business actions being taken. Don’t let them walk away from your establishment before they even hear about ‘Today’s Special’.
Worried about keeping your customers from leaving? Learn how your business can increase customer lifetime value (CLV) with retention marketing.
Ninisha is a former Content Marketing Specialist at G2. She graduated from R.V College of Engineering, Bangalore, and holds a Bachelor's degree in Engineering. Before G2, Ninisha worked at a FinTech company as an Associate Marketing Manager, where she led Content and Social Media Marketing, and Analyst Relations. When she's not reading up on Marketing, she's busy creating music, videos, and a bunch of sweet treats.
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