Archive for Rebecca Camus

Let's make the pie BIGGER! How to increase customer satisfaction and increase revenues with your data

Last week I gave a presentation on how Big Data and data from the IoT can help businesses improve customer satisfaction levels throughout each part of the customer life cycle. Today’s customer, no matter the industry, expects to have a positive and personal experience with companies even before there is a formal relationship. After they become a customer or register on a website, they expect a higher level of personalization and engagement and to be rewarded for their loyalty. Throughout the presentation (which can be viewed on our YouTube channel), there were three themes that were repeated multiple times no matter the life cycle stage or industry example.

The first theme was to collect as much information about the customer and her preferences as quickly as possible. This is especially important before you have an official relationship with a customer. Well, you might ask, how can you collect information about a customer if you don’t know their buying preferences or even know who the customer is because they haven’t registered with your company? Each smartphone and computer is equip with a unique machine id. When you implement a Big Data or IoT solution it’s critical to record the machine id with either the potential customer’s pathways around physical store or browsing history on a website. Also, its critical to record as much information as possible. Don’t stop with just what pages a customer visited on your site. Record how much time a customer spent on a specific page (a longer visit probably means they’re reading the description and interested in that product or service), how far did they scroll down the page (you’ll know what they read and where they stopped), and if they scrolled through the product pictures. All of this information can then be used to make personalized recommendations if the customer returns to the website in the future from the same device. Also, if a customer does eventually register from the same device in the future, the information you collected about them in the past can be added to her new account.

The next thing you’ll want to include in a solution is to ensure that all interactions are made in real-time while the customer is in the store or on the website. This serves two purposes – first it makes the customer feel like they are getting personalized service, they’re becoming aware of products that they might not know about and that the company cares about their satisfaction levels. However, it also gives the company a chance to either up-sell or cross sell the customer --- thus in the words of one of my favorite marketing professors, making the pie bigger for everyone. If the interaction happens after the customer leaves the store, the chances of that customer returning to the store for that additional item or to take advantage of the promotion are much lower. Real-time responses are also very important not only while a customer is browsing through a store or website but also if a negative experience happens to the customer. This is especially important with the popularity of social media. It’s too easy for a dissatisfied customer to go to Twitter or Facebook and post a negative message about your company. You want to be immediately aware of the disservice and correct it before a customer has a chance to go to one of these outlets and post about their negative experience. A real-time message or correction from the company can prevent this whereas if the company waits even an hour or two the dissatisfied customer can post online and the damage to the company with that customer and all of the customer’s followers is already done.

Finally, there needs to be a balance of personalization with a respect for an individual’s privacy. Over the past month two of my neighbors have told me of how their Facebook account knew a little too much about them. In one case, a neighbor mentioned to his wife while he had his phone out that they should look into getting a Dyson --- there were no internet searches or visits to Dyson.com, just a mention to his wife about getting a Dyson. The next day there was a Dyson ad on his Facebook account. He was immediately “creeped out” by the fact that somehow his conversation had been processed by his phone and was then reflected in a Facebook ad. He immediately deleted Facebook from his phone. As a company, you need to remember that people want personalized yet not intrusive recommendations. It’s a tough balance at times, but it’s critical to the success of your Big Data or IoT solution.

By keeping these three takeaways in mind your solution will help nurture and maintain customer relationships.

Entrigna provides consulting services to help evaluate your system and its Real-Time Expert System platform is the only solution platform on the market that incorporates all of the major big data related algorithms in one seamless solution. We specialize in healthcare and retail solutions, but our technology let’s clients, no matter the industry, start small and then add-on or change their solution as their business needs grow and change. For more information on Entrigna’s consulting services or RTES platform visit our website at Entrigna.com or e-mail us at info@entrigna.com

Yes, I meant to say prescriptive

I arrived a few minutes early to a presentation on IoT Security a few weeks ago and introduced myself to the man sitting next to me. He asked what the company I worked for did and I responded “We’re a real-time prescriptive analytics company.” He looked at me and asked “prescriptive?” I get this quite often --- most people think I’m mispronouncing predictive. Don’t get me wrong, we can do predictive analytics, but prescriptive is our specialty and the way of the future! When people correct me, I have to explain that no, I really meant to say prescriptive. This of course is followed more often than not with a blank stare as I explain the differences between predictive and prescriptive. To most people the difference in those few letters doesn’t mean much. However, in reality there is a huge difference!

Well, what’s the big deal in saying your software is predictive instead of prescriptive? Predictive analytics does just that --- it predicts. It predicts when something is going to go wrong. So for example, I’ve just created a smart refrigerator  – it can tell you’re going to run out of oranges on Tuesday, that the milk is expiring Monday and when a part is going to go out in the next 72 hours. However, that’s just it --- it predicts when these events are going to happen. It doesn’t solve anything. If it was a refrigerator that incorporated prescriptive analytics, it would not just predict these events, but solve them – hence the prescribing. So, my new refrigerator would re-order oranges and milk on Instacart and have them delivered and best of all it would fix the broken part or correct what was causing it to mal-function. So, all in all, a prescriptive solution prescribes remedies to a problem that is occurring or will occur. It doesn’t just predict when things are going to happen.

So, at the presentation, I was getting ready to launch into my speech, but I didn’t have a chance. As soon as I said “Yes, prescriptive,” the man smiled and said, “That’s what my group does too! Whenever I say it, people think I’m mispronouncing predictive.”  Maybe the prescriptive future will be here sooner than I thought!

Hidden revenue streams for smart cities

Today, many cities are toying with the idea of becoming a “smart city” or a city that actively does everything from monitoring traffic patterns to predicting when a street light will go out to analyzing any digital information its collecting. However, while these are nice to know items that can make life easier for inhabitants, lower emissions and can help reduce costs by improving efficiencies, many times these incremental savings are not enough to justify the large upfront cost of outfitting multiple items throughout a city with sensors. Not only are the upfront costs of sensors and their installation high, but also there is typically a resistance to change from city leaders who are nervous about changing their current processes and taking on the risk of implementing a “high tech” project. As a result of this, smart city managers and project owners need to be able to justify high expenses by having a measurable ROI and ensure that the city will also be able to generate ongoing revenue from these improvements rather than just decrease operating expenses.

One way to generate revenues is similar to what Kansas City (MO) has done. Kansas City installed kiosks throughout a city with maps and local information for restaurants, attractions, events and shopping. The kiosks have the potential to generate several streams of income while collecting important information. Initially, installation of the kiosks can be paid for or subsidized by a semi-permanent advertiser that can display an ad on the outside of the kiosk. Thus, there is little or no cost to the city to install the kiosks. As for the ongoing revenue, the city can sell advertising space on the screen to different advertisers who can run ads or offer coupons to users.  In addition to this, users can purchase tickets to attractions, events or public transportation from these kiosks. A small fee can be charged to the company selling the ticket. Next, the information collected from the kiosks, such as what attractions/restaurants/events are being searched for or how many people or cars are passing the kiosk can be sold to businesses in the area.  These different revenue streams should not only pay for the upkeep of these machines, but also generate extra income for a city.

Another way to generate income deals with using the information that people are voluntarily giving to governmental agencies online. Many people would rather complete forms online rather than go to a government building, pay for parking, wait in line and many times realize after they’ve done all of this that they’ve left an important piece of information at home. More and more cities are allowing inhabitants to do many tasks such as renew a license plate or city sticker online. People would probably even be willing to pay a small convenience fee to complete these services online. However, even without this convenience fee, if governments can turn the information they’re collecting online into usable data insights and not just a big dump of data, local municipalities could then generate streams of revenue selling these insights. Also, if they could determine what type of person is using their websites they could display targeted ads on their websites, which would generate another source of revenue.

Smart city initiatives can be extremely beneficial to inhabitants, local businesses and the environment, however, they can be expensive to implement. When a city is planning on starting a “smart city” project, they should try to think outside the box for revenue generating opportunities rather than just how much money will be saved through increased efficiencies. In a smart city, the possibilities are endless for saving money, improving the locals and tourists’ time in the city, minimizing environmental impact and also generating new streams of revenue.

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 info@entrigna.com.

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 info@entrigna.com.

 

 

Big Data in Agriculture

Over the next few months, I'll be writing blogs on some non-traditional industries that use big data. I'm looking forward to sharing updates and information on how big data can be used in all industries, not just the ones we typically associate with technology.

Farming is something most of us take for granted. We go to the grocery store and pick out our food without giving much thought to where our food came from or what went into growing it. We think of small quaint farms where farmers plant seeds, ride small tractors and then harvest their crops. However, many farms in the United States rely heavily on technology and are turning to big data to help them become more efficient, cost-effective, and less environmentally impactful.

Today’s tractors not only use sensors to collect information that help with preventative maintenance, but tractors also have multiple computer screens and sensors on them that collect information from everything from nitrogen and pH levels in the soil to how far apart the seeds are. Farmers tend to use this information while planting, however, many farmers do not use the information they’ve collected after the fact.

Farmers are also using “precision farming” to help make farming more efficient. This technique can mean many things, but ultimately it means using information about the soil and crops in a specific area to maximize the output of the crop and minimize the production cost for a crop. Farmers can use this information for everything from identifying the best places to plant certain crops to how many plants per acre they can plant.

In the future, we can expect to see more farmers adopting precision farming and other big data techniques. The big data market for agriculture is expected to grow from a $2.4B industry in 2014 to a $5.04B industry in 2020 (Research and Markets Global Precision Agriculture Market 2014-2020) and with the population projected to grow to 9 billion people by 2050, farmers will need to increase outputs significantly to keep up with demand. We’re already seeing some very interesting ways that precision farming and big data solutions us can be implemented at larger facilities. For example, Gallo Winery recently implemented a system that takes satellite imagery of their vineyards and determines which plants are getting too little or too much water. The images are processed, analyzed and then the sprinkler that is connected to an individual plant is automatically adjusted to give it either more or less water.  Water consumption at Gallo Winery has been reduced by 25% since the system was implemented, the health and production of the plants has increased and the costs associated with workers manually watering individual plants has decreased.

The real power of big data will be when farmers start sharing their data with companies. In the past, farmers have been very hesitant to share the data they collect to corporations. Many farmers view the information from their fields as propriety and are worried that the information generated from their farms will be shared with commodity traders or other farmers. They are also worried that seed and equipment companies will use the information to sell farmers higher prices goods. However, seed and equipment companies need information from individual farms in order to improve their software and products so farmers can keep achieving the best results possible. In the next few years, I believe seed and equipment companies will start focusing on how to earn the trust of farmer and proactively show farmers how sharing this information will lead to substantial ROIs for the farmers. Also, as time progresses farmers will become more comfortable with big data and the technologies and realize that the payoff of higher yields and ultimately lower costs will persuade farmers to share their data.

Trends in Big Data and the IoT in 2016

As we enter the new year, it’s always an exciting time to reflect upon the previous year and ask “What new things will happen next year?” Over the past year, it’s been really cool to see how executives at companies are realizing the value of using big data instead of just collecting it.  Because of this trend, 2016 should bring about disruptive changes in the big data and internet of things markets.

Some of the top trends in 2016 that I see happening are

Customer satisfaction levels will be influenced by an automatic personalized experience

As consumers become more tech savvy and more millennials have discretionary income, more consumers will continue to adopt and use mobile apps such as Target’s Cartwheel or PriceGrabber while they’re shopping. These consumers are looking for a personalized experience that will give them some benefit, whether it’s a lower price or targeted advertising or coupons based on past behaviors, when shopping. Consumers have many options to choose from when shopping both online and in-person and will ultimately pick the store that gives them the most value and the best shopping experience.

Additionally, with the increase of internet shopping and the multitude of stores available to consumers, companies will start relying more on what an individual is clicking on and posting on-line about products and her shopping experience. In the past, companies have had challenges making sense of this information in a timely manner and then reacting. However, companies are starting to discover solutions that can help them not only react in real-time to a customer’s shopping experience but also personalize the customer’s shopping experience based on past behaviors or trends. These proactive actions should lead to higher level of customer satisfaction for the customer.

Using ROI in big data

Executives are pushing for the adoption of big data solutions however, many executives want to see a measureable ROI and meaningful use cases before they make a large investment in a solution. In 2016, solution providers will start partnering with their users to determine the ROI of using a solution. Many times these measurements can be straightforward, such as calculating how much revenue is saved when using data sensors to predict when parts will wear out.  However, calculating the ROI on other solutions that combine structured and unstructured data will be more challenging to determine.

Data in the Internet of Things will start to be used instead of just collected

Sensors on many devices will help companies predict when parts need to be serviced and can also predict anomalies in the overall system. However, many companies have yet to realize the full potential of this data. In 2016, more companies who collect this type of information will no longer just store it but start to use this information to help prevent down time and achieve better customer service. Also, with the increased adoption of personal healthcare devices, such as Fitbits and smart watches, more consumers are going to start tracking their own healthcare.  Companies that provide solutions that monitor and make recommendations on a consumer’s heart rate, blood pressure or fitness activity will grow.

The need for simplified Big Data

Currently, many of the traditional big data solutions that make real-time decisions require users to be very tech-savvy and require substantial coding. However, in 2016, we will probably see more companies purchasing tools that can be easily used by non-technical users. This is because there is currently a shortage of data scientists and the average salary of an entry level data scientist is quite high compared to that of an entry level analyst. Many companies just can’t afford to have data scientists on staff.  Also, customer facing groups want to be able to see results in real-time and not wait for the IT or data science group to get them the information they need. Solutions will still need to be set up by data scientists and software engineers, however, once the solution is set up, non-technical groups such as marketing and customer service will be the ones accessing the data and writing simple queries to find the information that they need in real-time.

2016 will definitely be an exciting time for big data! The Entrigna team is looking forward to working with companies in the next year to discover how we can help them make and achieve their big data goals! For more information on Entrigna please e-mail info@entrigna.com.