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The Importance of Real-time Prescriptive Solutions in the Customer Lifecycle Management in the Airline Industry


In the last few weeks, the news and the internet have been filled with stories about the lack of customer service in service industries, especially the airline industry. Many companies in the service industry often forget that they’re in the customer business and take their patrons for granted. No incentives are offered, no customer engagements are made and no “surprise and delights” are given to reward customers for their loyalty.  What so many companies don’t realize is that if positive interactions with their customers aren’t made, it is too easy for customers to leave for competitors or tweet negative feedback for the world to see. This is especially relevant in industries, like domestic airlines, where there are many competitors that offer similar services. If customers are dissatisfied with a certain airline, many times there are multiple alternative airlines that offer similar routes. Because of the prevalence of competitors and easy access to the internet to search for other options, service oriented businesses need to be extremely conscientious about their customer lifecycle management and ensure that customers are having positive interactions with them through all steps of the lifecycle. If companies do not, they put themselves at risk for losing customers.

So, what is customer lifecycle management? The customer lifecycle consists of the acquisition, conversion, retention and loyalty of customers. This lifecycle needs to be closely monitored by marketers – however, this can be challenging because to effectively do this, a marketer needs to ensure that all relevant data is being collected about each potential and current customer. This data then needs to be interpreted and immediate personalized engagement needs to be made. This is particularly challenging because with more customers shopping online or using mobile apps, huge amounts of data are being generated every minute. Prescriptive solutions need to be in place to not only collect this information, but also to interpret that data, to identify what information is relevant and then automatically use this information to engage with the customer.

Real-time prescriptive solutions take data from multiple sources and then in a “non-scripted” way, interact with a customer as they’re in a store or experiencing a service. So for example, let’s say a platinum status airline customer is on a flight that gets delayed. This passenger has been on 3 other flights in the past 2 months that have gotten delayed. The solution would look at the historical and current information and proactively schedule the customer on the next flight. Depending on what the customer has set in his preferences, the customer would also be rewarded with a $100 voucher, an upgrade for himself and his traveling companions or additional mileage added to his frequent flyer account. A similar customer who may have had no other delayed flights in the last 2 months would be presented with offers that are less in value like a $25 voucher. A customer with no status and 2 previous negative interactions may only receive a free drink voucher.

Prescriptive analytics can also look at the overall patterns that a customer has. For example, a customer prefers window seats and always orders tomato juice on morning flights. However, when returning home this same customer will order an alcoholic drink and is likely to upgrade to business class. If a solution is implemented, flight staff can be alerted to this and “surprise” this guest on a night flight with a free drink. An alert can be pushed to this customer before his flight to purchase an upgrade at a discounted price, thus ensuring that he gets the business class seat that he wants. These proactive engagements will not only make the customer happy but also allow the airline to upsell the customer and ensure that a positive interaction has occurred.

These examples were just for current customers, however, airlines and other service industries can use real-time prescriptive solutions throughout each step of the customer life cycle. These positive interactions will be critical to the success of airlines and other companies in the service industries in the foreseeable future. For more information on how customers can be engaged through each step of the customer life cycle or our real-time prescriptive analytics solutions, please e-mail me at



Oh the Places You'll Go.....with IoT

Last week we attended the IoT NA conference in Rosemont, IL. As I stood at the booth I was amazed at not only the number of regional companies that were attending but also the different industries that were represented. I spoke to people from traditional industries like automotive and tech manufacturing, but I also spoke with attendees from a children’s museum, a drone company and several small cities across Illinois. Conversations with these people from “non-traditional” sector really got me thinking about how IoT can be utilized in pretty much every sector and the first movers from non-traditional industries will not only be able to give themselves an unbelievable competitive edge but also provide an incredible experience for their customers.

When the attendees from the museum came by, I could tell that they were on a scouting mission. They definitely recognized the value of using data from IoT, but were unsure of where to start. It makes sense --- when looking through the agenda of this conference there were fantastic sessions on sensors, the power of analytics and even monetizing IoT data. However, most sessions were aimed at manufacturing, because of course, manufacturing with its preventive maintenance and process improvements is the current leader in IoT projects. However, it may have seemed like a one-sided conference, however, many of the principles discussed can be applied to non-traditional industries. For example, many museums already have apps. Museums could use geolocation on the user’s phone to track how people are walking through the museum. This information, just like data collected from forklifts driven around a distribution center can be used to see who is traveling where, where people are stopping and how many people are visiting exhibits during certain time periods. This information can be invaluable to a museum (or a store or an airport and the list goes on….). It can show designers if current pathways are intuitive, identify which parts of an exhibit are the most/least popular and create better pathways for guests. If this information is utilized, exhibits can be tailored to what patrons are really interested in and also make sure patrons can easily navigate through exhibits – thus a happier guest who is more likely to return. Additionally, museums could combine information from a customer’s past navigation history and purchase history with their current location in the museum or even time that they’re in the museum. In real-time the app could make recommendations to the patron for special events occurring that day (for example, a lego building session for a family that has previously purchased legos or walked through a lego exhibit in the past) or current sales in the gift store when they are getting ready to exit the museum.

At the end of the day, non-traditional industries will not have out of the box solutions targeted to their specific needs. However, with research on what other industries are doing and a little creative thinking non-traditional industries can make very powerful and differentiating solutions. To take a page from Dr Suess these non-traditional industries needs to think about all of the places they can go…..with IoT.

For more information on how to get started with an Internet of Things project, please visit our website or e-mail us at

IoT in Transportation and Logistics

Recently, the idea of data and artificial intelligence has been making its way to the forefront of the news, especially in the form of driverless cars. However as frighten as this seems to many people, big data and the Internet of Things can play a very large and beneficial role in improving transportation and logistics without getting too Sci-Fiy for the average American.

So how can big data and the IoT help this industry? Well, obvious answers involve preventive maintenance. Don’t get me wrong, preventative maintenance is a great thing. By predicting when a part is going to break you can proactively replace it or service the machinery whether it’s an 18-wheeler or a piece of machinery. By having preventative maintenance as part of your business strategy, you’ll ultimately have more uptime which leads to higher revenue. However, this is so 2016. Preventative maintenance is just the tip of the iceberg when it comes to using the IoT in Transportation and Logistics.

One other idea on how companies can use IoT to streamline their processes involves prioritizing emergency calls. Many companies rely on dispatchers to get their service technicians to a call as soon as possible. However, when many service companies get a call to respond to an emergency, the dispatcher sees who is free in the area and then picks a person to respond to the call. Typically, there is not an automated process not only to identify what technicians are in the area but also how certain conditions such as weather, traffic or construction could possibly effect how long it would take the technician to respond to a call. In theory, a technician a mile away from a call could take much longer time to respond if a road is closed rather than another technical who may be ten miles away but coming from the opposite direction that doesn’t have traffic. The IoT can help solve this challenge. By combining current weather, traffic and construction conditions with the location of the technician, companies can automatically identify which technician or responder would make it to the call in the shortest amount of time.

The power of the IoT can also be seen by the use of RFIDs. RFIDs are tiny sensors that many parts and products are labeled with. Many companies use RFID technology to reactively manage inventory. So, when a company “does inventory” employees are told how many items are on a shelf instead of manually scanning each item on the floor and in the stock room (that was always my least favorite part of my college job at Banana Republic). However, the real power in these little chips is the ability to proactively manage your inventory. By using RFIDs, employees can be alerted when inventory levels are running low. Items can either be restocked from inventory or re-ordered. For more cool ways to see how RFIDs can be used in a logistics setting, check out our video on how the IoT is Revolutionizing Manufacturing.

For more information on how to get started with an Internet of Things project, please visit our website or e-mail us at



A New Way to Engage Customers With Real Time Decisions

Most merchants miss a huge opportunity to intelligently engage in real time with their customers.  Capitalizing on this missed opportunity could deliver 3% to 5% revenue growth through increased transactions and reduction of customer churn.

Traditionally, merchants have engaged shoppers through pricing, promotion and loyalty program tactics delivered through marketing campaigns and customer service.  Highly effective marketing organizations would take the data and insight from the customer interactions to determine how best to optimize future marketing efforts (e.g., target audience, message, offers, promotion channel).

These practices are tried and true.  Improving execution against this tactics will continue to deliver results and no doubt should remain a focus area for marketing organizations, especially with access to Big Data as an input into the analytics.  However, this engagement model is static by nature with periodic batch updates.

Real time decision capabilities enable marketing organizations an additional way to engage customers.  This is based on "in the moment" intelligence that dynamically determines an optimal action to take in real time.  Although current personalization tactics are a simple example, robust real time decision capabilities go well beyond it, delivering significantly higher effectiveness.

Where Real Time Decisions Sit in the Customer Engagement Model


Entrigna Blog - Customer Engagement and Real Time Decisions

Role of Real Time Decisions in Customer Engagement

Whether initiated by a marketing campaign or the customer, "events" occur all the time where a customer interacts with the merchant.  A basic example of "events" is when a customer enters a merchant channel - i.e., visit website, use mobile app, enter store, call contact center.  At that moment, the merchant has the opportunity to optimize the interaction with the customer.  Desired outcomes could be any combination of

  • Close a sale that was initiated but not completed in another channel
  • Optimize offers presented to drive transactions
  • Recognize key customer lifecycle milestones
  • Deliver excellent customer service - either surprise & delight or recovery actions.

In addition, once a customer interaction reaches an outcome (e.g., purchase, loyalty accrual/redemption, customer service resolution, abandonment), the merchant has another opportunity to re-engage the customer to drive additional desirable behaviors or outcomes.  This cycle could repeat continuously.

Beyond just capturing the "event" itself, real time decision capabilities leverage additional data to help determine an optimal action.  This data could be from both internal and external sources - e.g., customer profile, transaction history, prior channel activity, weather, geo-location.  Sophisticated and flexible decision intelligence frameworks (e.g., machine learning algorithms, complex event processing, optimization techniques, rules engine) are prerequisite tools to derive intelligence (for more detail on required real time decision capabilities see How to Execute Real Time Decisions).

When you step back, real time decisions is an automated, algorithmic means to engage customers in a similar fashion that store clerks have been doing for ages.  However, because of the automation, the capabilities can pull in large amounts of data to feed "intelligence" and work in 21st century e-channels like mobile.

Tell us what you think?  We'd love to hear.