Data mining examples

Data mining examples show the process of discovering patterns and identifying rules in large data sets. Machine learning, artificial intelligence, statistics, and database systems are methods frequently used.

How data mining is applied across industries is vastly different. That’s because the goal of data mining is understand customer behavior, predict future behaviors and identify steps that accelerate the desired outcome. And customers behave differently depending on the industry.

To show how, here are 10 data mining examples for 10 different industries.

Banking data mining

In banking, the main objective is to use data mining is to extract valuable information from distinct customer data. That’s because the key strategy for a bank is to reduce costs and increase bank revenues. The customer, and their accounting and personal information, is the backbone for data mining examples of every bank. They collect data such as their purchase history, geo-location preferences and other behaviors. Bank that effectively use this data mining analysis to create right product for the right customer.

E-commerce

Many e-commerce companies use data mining and business intelligence to offer cross-sells and up-sells through their websites. One of the most famous of these is, of course, Amazon, who use sophisticated mining techniques to drive their, ‘People who viewed that product, also liked this’ functionality. By thoroughly studying and analyzing past data and behaviors, Amazon categorizes products depending on the probability of your purchasing the product.

Educational data mining

Educational Data Mining (EDM) is increasing rapidly as more and more education systems are going online. It has opened new areas like new computer supported interactive learning methods, tools-intelligent tutoring system and simulation games. This has created opportunities to collect and analyze student data , to discover patterns and trends in those data and to make new discoveries and test hypothesis about how students learn through online classes. The data collected from online learning systems can be aggregated over large numbers of students and can contain many variables that data mining algorithms can explore for model building.

Healthcare

Lab tests are often essential to enable a health care provider to decide how to treat a patient. Applying data mining helps doctors discover things they might otherwise miss within laboratory results. In one study, researchers looked at more than 600 urine samples and used data mining to classify patients by life expectancy based on characteristics of their urine. Taking this approach reveals instances where patients are sicker than they seem, allowing doctors to take prompt action.

Marketing data mining

Data mining in marketing is used to explore increasingly large databases and to improve market segmentation. By analyzing the relationships between parameters such as customer age, gender, tastes and lifestyles, it is possible to predict behavior in order to direct personalized loyalty campaigns. Data mining also predicts which users are likely to unsubscribe from a service, what interests them based on their searches or what a mailing list should include to achieve a higher response rate.

Mass merchandisers

Mass merchandisers are good data mining examples in action. Loyalty card programs are usually driven mostly, if not solely, by the desire to gather comprehensive data about customers. One notable recent example of this is Target. As part of its data dining program, the company developed rules to predict if their shoppers were likely to be pregnant. By looking at the contents of their customers’ shopping baskets, they were able to spot customers who they predict were likely to have a baby on the way. They then send them targeted promotions for diaper, wipes and other baby products. Their predictions were so accurate that Target made the news by sending promotional coupons to families who did not yet realize (or who had not yet announced) they were pregnant! 

Mobile phones and utilities data mining

Mobile phone and utility companies are data mining examples that predict ‘churn’, the terms used for when a customer leaves their company to get their phone/gas/broadband from another provider. They collate billing information, customer services interactions, website visits and other metrics to give each customer a probability score, then target offers and incentives to customers whom they perceive to be at a higher risk of churning.

Nursing

An analysis reveals a substantial portion of Medicaid patients are going to the ER more than 10 times per year. 2 or 3 trips to the ER is just a bad year, but more than 10 visits means that something has gone wrong. This prompts Medicaid employees to call these patients, take steps to increase their level of personal care at home and institute 24/7 nurse hotline to allow Medicaid patients to call in for medical help rather than going to the hospital. This lowers the costs of Medicaid ER visits by more than 20%.

Retail data mining

Retailers segment customers into ‘Recency, Frequency, Monetary’ (RFM) groups and target marketing and promotions to those different groups. A customer who spends little but often is handled differently to a customer who spent big but only once and some time ago. The former may receive a loyalty, up-sell and cross-sell offers, whereas the latter may be offered a win-back deal, for example.

Social media

A study published in the Journal of Advertising uses social media mining techniques to gauge users’ perception of a variety of common brand names. The study specifically looked at Twitter, examining tweets of brands in the following industries: fast-food restaurants, department stores, telecommunication carriers, consumer electronics products, and footwear companies. The researchers use the Twitter handles of each company (“@CompanyName”) as keywords to pull about ten million tweets for each of the twenty companies studied for results that are incredibly specific. For example, the study found 15.7% of tweets about fast-food restaurants are about promotions chains are offering. And, among cable companies, 66.7% of tweets about Comcast contain a negative sentiment.

Are these relevant data mining examples to you? Could you use guidance on data mining for your company

Negative online reviews

The Internet provides consumers with nearly unlimited options and a direct channel for communication with companies. Love a product’s design and functionality? Write a review on Google. Experience negative custom service at a restaurant? Share it on Yelp. Negative online reviews can be shared too.

Online reviews can make a significant impact on the future of a company given that 89% of consumers read a company’s reply to reviews. Therefore, a business should spend time carefully crafting their reply to both negative and positive reviews. 

Many people consider negative reviews to be inevitable because not one consumer values or experiences a product or service the same. Ignoring consumer reviews online can hurt your brand and cash inflows. Read on for tips for replying to reviews online.

1. Recognize the Problem and Apologize

We’ve all heard the phrase “the customer is always right.” Take that to heart when replying to a negative review. Acknowledge the problem in your response, so the consumer knows you understand and include an apologetic sentence or two. 

Customer complaints can be perceived as ridiculous from a business standpoint, but their feelings are real. De-escalating the situation with an apology is all the consumer wants sometimes.

2. Empathize

At the end of the day, we’re all human. Display your compassion in your reply to a review, so your customers know you care above and beyond the transaction. Put yourself in their shoes and ask how you’d feel in this situation. This can be a good exercise before drafting a response.  Here are 12 authentic ways to get better online reviews.

3. Avoid Disputes Online

An important guideline to replying to negative reviews: it’s not personal. Running a business requires tremendous energy, hardwork and heart. This makes reading a negative review online frustrating for many business owners. 

Avoid defensive replies by taking a moment to breath and calm your emotions. Future customers may be hesitant to purchase your products if they see you’ve argued with past customers. 

4. Give Offline Support Contact Info

More often than not, negative customer reviews involve serious problems. If a customer simply doesn’t like the product, it’s unlikely they’ll spend time blasting their opinion online. Regonzie when a review needs more than a short reply and provide an email or phone number to directly reach someone for help. This proves your company values their business and goes beyond a mediocre “give us a call” page.

5. Implement Steps to Mitigate the Situation

A common step to mitigate a negative review is extending an offer. Some airlines extend offers to upset customers in the form of a discounted flight or free baggage, depending on the severity of a situation. This could win a customer’s respect and business back because it shows your commitment to excellent customer service. Ensure you acknowledge the problem and apologize before giving an offer because this could be perceived as bribery. 

6. Answer the Review with Gratitude

It may sound funny to say “thank you” for a negative review, but gratitude can turn a negative situation into a positive one. Most of the time ending on a positive note is a company’s goal when replying to reviews. Thank your customer for allowing you to solve any internal problems from their rear view. This can make a genuine and lasting impact. 

7. Update Your Reply

Some negative reviews involve a few messages back and forth with a customer. Once you’ve reached a resolution of a customer’s issue, include a status update that reads “resolved” to show future customers you took action. Ultimately, this promotes your customer service capabilities.  

Below is an infographic from Housecall Pro featuring examples and template ideas for you to practice writing your own negative review replies.

Drew is a content marketing specialist from San Diego, where he helps create epic content for companies like Housecall Pro. He loves learning, writing and playing music. When not surfing the web, you can find him actually surfing, in the kitchen or in a book.

Sales lead

Good sales leads are the foundation for any lead generation strategy, one of the most frequently used strategies in digital marketing, especially among B2B companies.

For a lead generation strategy to be successful, it makes sense for there to be clarity and alignment around the definition of sales lead.

Unfortunately, too many organizations lack a clear definition that can be used across marketing and sales. There are even differences among the experts.

So you decide best definition for your business, here are 10 experts that give their definition of a good sales lead.

1. “A lead is a person who has provided at least some basic information that suggests a potential interest in buying from you.” – Dan Purvis, Head of Marketing Communication, Planet
2. “A lead is an unqualified contact. Any potential client or customer you meet that hasn’t been qualified as a prospect, is a lead. A prospect is a potential customer that has been qualified as fitting certain criteria.” – Mindy Lilyquist, Founder, Epiphany Marketing Management
3. “Lead – An individual who has provided contact information and, in doing so, pointed toward a potential sales opportunity.” – Matt Leap, HIPB2B
4. “An individual or company with an actionable need for a service or solution.” – Dan McCade, President and CEO, PointClear
5. “A lead is usually a person who just entered your marketing funnel. He may have filled out your online form. Or signed up to your program. Or clicked on your ad. A lead’s engagement is usually minimal. They just showed interest, but they aren’t that invested in your product or service yet. A prospect, on the other hand, is a person who has been exhibiting interest or showing ability to make a purchase. A prospect has been qualified by your sales team or your segmentation process.” – Will Cannon, Founder at UpLead
6. “RULE No. 1: A good lead is pre-qualified. RULE No. 2: A good lead is easy to convert into a customer. RULE No. 3: A good lead is easy to close. RULE No. 4: A good lead includes quantitative data.RULE No. 5: A good lead is measurable and measured.” – Geoffrey James, CBS News, Moneywatch
7. “Most salespeople define a sales lead as a person or business who fits the perfect customer profile of their company.  A qualified sales lead is a lead that has been validated and checked manually within your organization (or by a third party) as meeting the minimum attribute level of the customer profile. This task is usually carried out by the marketing team. A prospect is a person or organization that has expressed an interest in your product or service.” – Liz Fulham, Sales Optimize 
8. “A marketing qualified lead (MQL) is a lead who has been deemed more likely to become a customer compared to other leads. This qualification is based on what web pages a person has visited, what they’ve downloaded, and similar engagement with the business’s content.” – Sam Kusnitz, HubSpot
9. “A sales qualified lead (SQL) is when the buyer has a defined project with budget and timeline established.” – Craig Rosenberg, Chief Analyst, TOPO,
10. “The point is: a “Lead” isn’t a sure thing. One of the dictionary definitions states that a lead is, “a slight or indirect pointing to something”. – Justin McGill, LeadFuze

Before your organization jumps into a lead generation initiative, make sure you have agreement on how you define a good sales lead. Do these definition help your consideration? Are you ready to begin?

Sales Funnels

Sales funnels are a series of steps designed to guide potential customers toward a buying decision. They are models of the customer journey a company uses to purchasing their product or service and to give them their best advantage.

The goal at each step of sale funnels is to solve customer problems and keep potential customers on the path to purchase.

Because when you know customer problems, you can present the solution, content, messaging or incentive that keeps them on the destination to purchasing your product or service. This is when the real magic of sales funnels happen. Or doesn’t.

10 experts explain what makes sales funnels succeed or fail.

What makes them succeed

• “The one thing is: lead nurturing. Let’s look at where customers are coming from. No matter how they get to you, as many as 73% of leads are not even ready to be sold to. Even from the pool that are qualified, half of them aren’t ready to buy. Companies who properly nurture their leads see a 450% increase in qualified prospects. And, those who take the time to nurture and grow those customer relationships, see 50% more sales at a 33% lower cost.” – Neil Patel – Entrepreneur, New York Times Bestselling author and top Influencer

• “Tony Robbins says that all human desire is based on one foundational principle. That principle states that we will always do more to avoid pain than we will to gain pleasure. This principle of pain versus pleasure can easily be leveraged by positioning your products or services in the right way to help leverage this strategically. When you think about pleasure, you can also think about the benefit. What’s the biggest benefit (pleasure) that a consumer is going to get when they buy what you’re selling. You also have to think about what they’re going to avoid (pain).” – Robert Kanaat – Author, Engineer, Blogger and Entrepreneur

• “They need to learn about your product and services. This goal can be achieved with the help of quality blogs, interesting video, involving influencers and conducting email campaigns. If people are not aware of the products you sell, there will be no sale. Therefore, you need to adopt different lead generation strategies to drive users to your website. Your lead generation efforts won’t be enough on their own if you fail to engage your audience. .” – Shane Barker – Digital Marketing Consultant

• “Sales funnel work when you know your target inside and out, including her biggest frustrations and deepest desires, in his or her words, have a clear offer that you know she wants, without a doubt, understand and know how to effectively employ marketing and sales strategies that can “speak to the masses,” and have a very high flow of traffic entering into your funnel.” – Jenny Shih, Business Coach

• “Landing pages are the first direct connection between your leads and your business. And, when the competition is stiff, the first impression is definitely the last impression, right? Target optimization and your promotional specifications must reflect the promise presented in the targeted ad your viewers clicked on.” – Sam Makad, Marketing Consultant

Why they fail

• “There a gap between sales and marketing. Your marketing manager is attracting followers and connections, creating white papers and e-books to attract leads, and optimizing the latest blog post. Your sales manager is assuring that every sales representative has the training to do what he or she does best—sell to a qualified buyer. But if no one is qualifying leads, there’s no bridge between these valiant sales and marketing efforts and the synergies are lost.” – Jeff Kalter – 3D2N

• “You aren’t bringing in enough traffic. Your sales funnel begins with the traffic that you bring in. If you aren’t bringing in enough traffic, then your sales funnel has no chance to work. If you don’t have enough visitors to your website or landing pages, then you won’t have enough subscribers. If you don’t have enough subscribers, then you won’t have enough (or any) sales. If you don’t have sales, then you don’t have a business. So before you try to optimize other parts of your funnel, you need to fix your traffic problem.” – Tonia Kendick, Solopreneur

• “The idea that customer journeys are linear (they’re not). Customers not only enter at all different stages but they often skip over stages entirely, move back and forth between stages, or will stay at one stage indefinitely. Don’t sit down and map out a step-by-step process that says “first they’ll do this, then they’ll do that, next they’ll do this…” and expect that your customers will actually follow your plan. Some reports are saying that up to 90% of the customer journey is now self-directed.” – Gary DeAsi, Director of Marketing, Demand Generation

• “Lack of consistent follow up. According to JMJ Direct, 48% of sales representatives never follow-up with a prospect. Furthermore, only 10% of sales involve more than three contacts and an incredible 80% of sales are made on the fifth to twelfth contact. Knowing the most appropriate time to contact a lead is difficult – do you start calling new leads or follow up on an old lead for the fifth time?”- Search Engine People

• “Not providing different content for every phase of the funnel. Newly entering customers have shown interest in your product and services, and simply want to explore. They want content that’s educational — different than the customers in the middle of your funnel who have taken a step beyond basic information and are looking for more details. It makes sense, then, that serving up the same content for every stage will only frustrate customers and totally mess with your flow. Provide relevant content — appropriate for every phase — that nurtures customers along instead of chases them away.” – Kelly Kalis, Revel

Do these experts provide insight for you on what makes sales funnels succeed or fail? Does your business need help creating a sales funnel that works.

Chatbot case studies

Chatbot case studies show the success of artificial intelligence (AI) programs that simulate interactive human conversation by using key pre-calculated phrases based on auditory or text-based signals. Chatbots are frequently used for customer service with marketing systems.

Chatbot case studies are also a demonstration of one of the more widely used applications of artificial intellence (AI) for marketing. Do Chatbots work?

• $8 billion will be saved by 2022 from businesses using chatbots according to IBM
• 85% of all customer interactions will occur through chatbots by 2020 according to Gartner
• 53% of customers would happily message than call a customer service agent

Here are 12 chatbot case studies that prove ROI and show the success of AI.

1. 1-800-FLOWERS: Used GWYN is a product of IBM’s artificial intelligence system, Watson, and is based on the Fluid Expert Personal Shopper (XPS) software platform). The chatbot helps consumers search for and place their gift order online. GWYN becomes smarter as “she” interacts with more customers over time; the eventual goal is to offer a customized shopping experience based on past buying behaviour. 70% of customers ordering through the chat bot were new 1-800-Flowers customers
2. AMTRAK: Has 20,000 employees and serves 30 million passengers per year. Amtrak.com receives 375,000 visitors every day. Through their chatbot, Julie, travelers can book rail travel by simply stating where and when they’d like to travel.  Julie has been designed to function like Amtrak’s best customer service representative, She answer 5,000,000 questions per year. With Julie, Amtrak has increase bookings by 25%. A booking through Julie the chatbot generates 30% more revenue. Julie has produced an ROI for Amtrak of 800%.
3. CHARTER COMMUNICATION: Is the second largest cable provider and the fifth largest phone providers in the U.S. Before switching to a chatbot service, Charter Communications had 200,000 live chats per month. 38% of these live chat conversations were for forgotten usernames and passwords. When they switched to a chatbot, it didn’t just take over those basic password and username questions. 83% of all of chat communications were handled by the bot. That’s 166,000 chat requests per month that Charter no longer had to worry about. And a 300% ROI within six months.
4. COVER GIRL: Recognizing the important role that l media influencers play in reaching beauty consumers today, Cover Girl creates teen-focused chatbot messaging app called Kik, modelled after Kalani Hilliker, a 16-year-old American dancer, model and TV personality. The bot interacts with fans in a fun and natural way and shared branded product information and coupons when the user expresses genuine interest in makeup and achieving a new look. The results are 14X more comments per post, 51% click through on coupons and 91% positive sentiment.
5. JOHNSON & JOHNSON: The BabyCentre UK website (part of the Johnson & Johnson family of companies) is a trusted pregnancy and childcare resource in the United Kingdom. From due date calculators to articles about self-care for moms to user communities, BabyCentre puts out a lot of content geared toward all stages of motherhood and its chatbot equally delivers. Much like its Facebook Messenger Bot, BabyCentre’s email marketing is also personalized and targeted. However, when BabyCentre tested whether its chatbot or email marketing drove more traffic to its website, the results were staggering. On average, the bot had an 84% “read” rate and a 53% CTR, 1,428% higher than email.
6. L’OREAL: The biggest beauty company in the world, launches an innovative messaging chatbot for Facebook Messenger called Beauty Gifter to improve personalization. Beauty Gifter gets to know each user’s needs and preferences and makes personalized product recommendations from 11 different L’Oreal brands, integrating with L’Oréal’s e-commerce system for checkout. It also proactively follows-up with personalized, relevant content, pushed at the right time, to drive on-going engagement. Beauty Gifter chatbot case studies result show 27X higher engagement than email, 31% rich profiling and 82% loved the experience.
7. MOBILE MONKEY: Easily creates chatbots that works through Facebook messenger. One of their tactics is to use a little-used Facebook ad type: the click-to-Messenger ad. They engage your audience on their own turf and reduce cart abandonment. For client, LeifTech, with only a $311 ad investment, they generated $14,975 in revenue and a 1133% increase in conversion.
8. REWARD STREAM: A referral marketing program, now a part of buyapowa, is doing everything right on the digital marketing front: generating traffic, engaging content, effective paid advertising and a solid email marketing strategy. They decide to invest in a chatbot that engage visitors at the opportune moment. RewardStream find they steadily converts a higher number of leads as the days rolled by – reaching an impressive 30% of all conversions with the first month and a half..
9. SALES RABBIT: Is a company that books meetings for sales teams. They use form that then exchanges emails between the rep and prospect, After switching to a chatbot, they are able to not only qualify leads but then immediately book time on their sales team’s calendar, SalesRabbit has a 40% lift in the conversion rate of requests to meetings held and a 50% increase in qualified leads.
10. TREE RING: Is a service for creating custom yearbooks online. Their sales team is able to produce quality, sales-ready leads. But most of their sales come from current customers who like to spend time on the phone with sales reps. This may be a nice problem to have but it also is a drain on resources. By automating the lead qualification process through a chatbot, TreeRing sales people can focus on closing sales. This results in a 15X ROI through a 10% increase in pipeline value.
11. VANARAMA: Leasing a vehicle is not a simple conversation. It’s an intricate, complex, and personal data-heavy process. Vanarama, the UK’s leading van leasing company, launched iVan, a full-page chatbot and a pop-up widget. iVan answers hundreds of frequently asked questions, takes users through an end-to-end van leasing journey, including credit checking and finance approval, close deals itself, without human intervention and hands over warm leads to human salespeople. iVan the chatbot closes over 500 sales and creates 30,000 leads.
12. WHOLE FOODS: Whole Foods’ Facebook Messenger Bot connects with users by providing recipes, products, and cooking inspiration. Presenting filters and options for different types of food, including international cuisines with each message, Whole Foods makes it easy for users to narrow in on the kind of recipe they’re looking for. Once enough filters have been selected, the bot presents a link to a specific recipe that directs users to the company’s website. Rather than rely on direct visitors, Whole Foods’ chatbot drives traffic to their site from a platform where people spend on average 50 minutes a day.

Do these chatbot case studies convince you of their ROI? Do they help you see how AI is being applied to marketing. Are you ready to talk about the future of your digital marketing?