06 - Week " Pinterest Business Model Canvas"

PINTEREST Business Model  Canvas

 What is Pinterest?

"Pinterest is a social network that allows users to visually share, and discover new interests by posting (known as 'pinning' on Pinterest) images or videos to their own or others' boards (i.e. a collection of 'pins,' usually with a common theme) and browsing what other users have pinned. Using a visual orientation, the social network is very much focused on the concept of a person's lifestyle, allowing you to share your tastes and interests with others and discovering those of likeminded people. The social network's goal is to "connect everyone in the world through the 'things' they find interesting." Users can either upload images from their computer or pin things they find on the web using the Pinterest bookmarklet."

Read more: http://www.infront.com/blogs/the-infront-blog/2014/1/20/what-is-pinterest-and-how-does-it-work#ixzz37x6qcblc

User market and Customer Segments:

General user:

Pinterest is 3rd largest social networking site after FB and Twitter with 46 million users and growing. 80% of the users on Pinterest are women between the ages of 18-35, 50% of them have children. They are Tech savvy, and are hobbyist and do-it yourselfers. 28% percent of them are affluent. Generally a user spends 16 mins per visit on Pinterest

Advertisers & Affiliate Partners:

Retail and online business that would like to advertize to the general users based on their interests and hobbies. Currently over 300 advertisers (Target, Macy's etc.. ) use pinterest to "pin" relevant ads to users. Blog users another affiliate partners use the platform to target the general user community with advertisements

Value Proposition:

Pinterest is unique as a Social network because it allows user to create online scrap books of their interests and share them with other friends and users. The users can also search other's billboards for similar items and and discuss and learn from each other. Users also use pinterest to discover new interests A 46 million strong community of mostly active users create a robust social experience for almost any interest or hobby.

Pinterest also provides a unique value proposition for businesses to advertise. It cuts out 1 or more steps in targeting the advertisement that are generally used on social websites like FB and Twitter. Generally a business needs to figure out what the customer is interested in by deciphering the posts and behaviors and likes and then target the advertisement to the user. In Pinterest targeting is much more straight forward. The user tells the business what they are interested in by posting pictures. Just by using pinterest the advertiser knows what the customer is interested in.

Ref:  http://www.businessweek.com/articles/2013-10-24/why-investors-love-pinterest-so-much

Financials:

Investments and Valuation: 

Total VC funding to date $746 million. Market Valuation based on funding and future revenue opportunities is a between $3.5 to $5.0 billion. 

Costs:

Pinterest has two main sources of costs. 

• 240 full time employee with annual wages to be estimated at $24,000,000
• Pinterest uses amazon's cloud service to backup the data the users are posting on the website. The costs of managing about 15million visits per month is estimated at $20,000. If we assume that 15 million of pinterest users visiting and posting to the site 4 times a month on average we can factor in $100,000 in monthly costs. Which translates to $1,200,000 annually for web hosting. 

Ref:  http://thenextweb.com/dd/2013/12/02/much-cost-build-worlds-hottest-startups/

Revenue:

The projected revenue for in 2014 is $11,600,000 with expected revenue growing to $500,000,000 by the end of 2016.

In our model we factored in 2 sources of revenue:

• Affiliate revenue: We 15 million users clicking through 4000 affiliate marketing sites would generate at $1000 in revenue per affiliate. This totals to $4 million annually through affiliate marketing. 
• Advertising Revenue: If users click through and purchase through the affiliate advertising we assume that Pinterest will make money off it as well. We calculated about $.10 in purchasing revenue per user. We factored in 80% of users being active on the site and interested in purchasing resulting in $7.6 million in revenue for advertising. 

Ref: http://gigaom.com/2012/03/30/how-much-does-pinterest-actually-make/ 

Based on these calculations Pinterest would make a loss of 13.6 million in 2014

Projected revenue growth in 2015 and beyond:

The revenue model in this domain is well understood. Google, FB and Twitter already make billions through affiliate marketing and online advertizing. With more users and affiliate programs being launched there is little doubt the Pinterest will become profitable in 2015. Pinterest's Pin boards are a natural fit for marketing using images. Additionally Pinterest allows for much better targeting of products to users who would be interested in them.This will allow for more revenue per click and also per purchase. It is not far fetch to expect revenue per user to grow to $10 (from the current $.10) on average, with 80% of users active this can amount to $7.6 billion annually

Additionally, there are several other revenue models that Pinterest can adopt to grow its revenue stream:

• Charging Customers:  User customer data to build its own online retail store and and target current customers 
• Charging Advertisers: Expand the branded pins to include branded marketing campaigns. Where Pinterest allows brands to create their own pages to post pin the products that represent their brands
• B2B Data Sales: Selling Pinterest user data to other business to help them target advertisements on Pinterest and other media.

Pinterest only recently started to make money through advertising. Revenue projection of $500 million by 2016 are achievable as the platform grow and advertising base grows.

Other references:

1. http://www.quora.com/Pinterest/What-meaningful-problem-does-Pinterest-solve
2. http://www.quora.com/Pinterest/How-does-Pinterest-generate-revenue-What-is-the-companys-business-model
3. http://www.infront.com/blogs/the-infront-blog/2014/1/20/what-is-pinterest-and-how-does-it-work
4. http://capitalistcreations.com/how-pinterest-created-its-own-niche-market-from-facebook-users/
5. http://harkable.com/blog/who-is-a-typical-user-on-pinterest/
6. http://www.circlesstudio.com/blog/is-pinterest-right-for-marketing-your-business/
7. http://online.wsj.com/news/articles/SB10001424052702304027204579334651169493632

05 - Week

This week's readings focused on how big data can be used to identify patterns that can be helpful in numerous ways. The Numerati disucsses a company that employes mathematician to sift through massive troves of online data gathered by people's interactions with technology to identify patterns and relationships that could be beneficial to advertisers. In an interesting example provided in the reading the author discusses how he found a correlation between people who had just watched a romantic movie and clicked a rental car ad banner. Mining big data provides us with these curious insites into human behavior. To make sense of why a correlation exists further analysis of data is needed. By analyzing data and understanding the relationships, companies create customer profiles that can be used to target customers with the right mix of product and service.

Big data analysis is not just for marketing and providing the right product, at the right time, at the right price to a customer. Data mining is used in the medical industry to understand causes of diseases. As the "Big Data and Your Health" article discusses, how using large pools of data gathered about patients, researchers can understand the specific genes that cause certain diseases. They can test their hypothesis through experimentation and data mining and then can formulate medical treatment plans and recommendations to lower (or even prevent) the probability of diseases in high risk patients. In some cases heightened surveillance is recommended for patients that have a certain predisposition to a particular disease. To make these recommendations medical researchers mine the vast quantities of patient data available in hospitals.

There are several algorithms and techniques available to help mine data. With increased computing power and web 2.0's propensity to collect masses of data; more correlations will be found and investigated. 6 years ago as a graduate student in Computer Science, I published a paper on a data mining algorithm called "Random Forests". This algorithm could be used to learn form data sets that are imbalanced (http://dl.acm.org/citation.cfm?id=1337332). As an analogy, the learner was trained to find a needle in a haystack. This is a classic example of working with big data to find root causes for a hypothesis. 8 years ago, I helped a Gastroenterology fellow at the Cleveland Clinic to validate the recommended age for first time colonoscopy. Similar to the study mentioned in the "Big Data and Your Health" article, we mined to 1000s of patient records to identify if there were any correlations between age, sex, race, gender, income etc.. and the presence of per-cancerours polyps in the colon. The study ultimately recommended that the first colonoscopy should be performed 10 years earlier than the current recommendation (the current recommended age for initial colonoscopy screening is 50). The abstract was published in the American Journal of Gastroenterology (430 Comparison of the Detection Rate of Colorectal Neoplasia by Colonoscopy in Average-Risk Patients Ages 40-49 vs. 50-59 Years )

Data mining has been a field of study for the last 10-15 years in computer science. The every increasing stores of data provide the Numerati with limitless possibilities in several disciplines form medicine, to advertising, to counter terrorism. Privacy hawks will consider the proliferation of big data as an assault on individual privacy. They may have a point as the NSA leaker, Edward Snowden's case has revealed. Ultimately we have to decided if the benefit that big data brings us out weighs the potential privacy violations that can occur. The current trend in the Web 2.0 world seems to be headed in the direction of creating ever more data that can be used to benefit (or harm) large segments of humanity.

05 Week - Business Model Canvas

The above business model canvas is for residential burglar alarm (BA) monitoring and home automation (HA) company.

The value proposition the company is that it provides intrusion monitoring for residential units. If a intrusion were to take place in a home that was monitored the company, the company would call the police and request dispatch. The company also provides home automation services where in addition to controlling lights, heating and cooling, the BA (burglar alarm) system can be armed and disarmed remotely. The key value proposition is the integration of BA and HA systems for customers that have both systems, so that the customer can program home automation responses in the event of a burglar intrusion into a home.

The company sells the BA system as a basic system and upsells the home automation components. The company sells its system either directly through its web site and on the ground sales force, or indirectly through a dealer network. The installation and hardware of the BA and HA systems are significantly subsidized. The customer is required to sign a 3 year contract and is charged a monthly subscription fee for monitoring. The fee is $40 a month for BA monitoring and $75 a month for BA and home automation. The 3 year contract is designed to ensure that the subsidized hardware provided is paid off and the company has  net positive revenue at the end of the contract term. Early disconnects carry an early termination fee. This model is very similar to the consumer cell phone purchase model by AT&T and Verizon.

The company does not manufacture the systems it sells, thus key partnerships are formed with manufacturers of BA panels and home automation equipment. Prices are negotiated based on bulk pricing due to significant economies of scale. These lower prices are necessary to reduce the subscriber acquisition costs (discussed later). 

The total market for BA systems is $13 billion and the total market size for Home automation is $14.5 billion. The competitive landscape has a few large players but no single company controls more than 5% of the market with a over 90% of the market still untapped. The company presented above aims to control 5% of the market for BA systems and hopes to increase revenues to $7.5 Billion. It hopes to tap 2% of the HA market and achieve revenues of $4billion. The segment size for BA is 300 million customers, and for HA systems it is approximately 200 million customers.

Costs structure is broken down into 3 key costs:
Subscriber acquisition costs (SAC): This is a variable cost dependent on each new sale. It includes marketing, sales, and equipment costs. The largest portion of the SAC is the subsidy on the equipment that is provided to the customer. Subsidies on BA systems are higher than subsidies on HA systems. These are calculated as percentage of the each sale and monitoring revenue over 3 years.
Monitoring Costs: These are costs involved in standing up and maintaining monitoring facilities to monitor and dispatch police if an intrusion event takes place. The costs are largely IT and resources. These are fixed costs and approximate about $1billion (or 10% of revenue)
Installation and Service Costs: These are costs related to have a large field support team in place. It includes installation equipment and vehicle expenses and the costs of the installers labor. These are also a fixed cost and are about 10% of revenue or $1billion.

Total costs for the business over 1 year is approximately $7 billion on expected revenues of $11.6 billion. EBIT is projected to be approximately $4.5 billion.

The keys to customer relationships are:
Retention: If a customer is retained past the 3 year contract term, the overall cost per customer is dramatically reduced as the SAC cost of that customer is totally recovered. Retention is key to increasing profitability
Acquisition: Due to the high fixed costs of monitoring and maintaining a large feet of installation and service technicians, an increase in customer base is necessary to reduce the overall fixed cost per customer. Acquisition is also necessary to gain market share.
Customer Service: Is necessary to ensure timely dispatch in the case of a intrusion event and verification with the customer that a false alarm event is not being reported. 

04 Week

This week we discuss new business models that have been enabled by Web 2.0. We start with the "Dollar Shave Club." I am can personally attest to being sick of paying high prices for razor blades and switching to a more cost effective (older) way of shaving using a double edge razor. The genius of the dollar shave club lies in using Web 2.0 for marketing and gathering a customer following of the concept. Subscription also is enable through the website, however the logistics and delivery of the weekly shaving kit relies on old fashioned logistics to deliver the product to the customer's home. Recently, I noticed an advertisement from a company called The Trunk Club, with a very similar business model. The advertisement I saw was on Facebook as part of my News Feed. The company serves a slightly affluent male clientele who does not have a good dress sense. The business requires it's clients to sign up online at which time the person is assigned a personal stylist. The personal stylist calls the client and discusses the person's tastes. He/she then puts together a "Trunk" of designer clothes that are well coordinated and ships it to the client. The client is free to try all the clothes at home and keep what he like before sending back the remaining Trunk to the company. The client is charged only for the clothes he keeps and shipping is free both ways. The Dollar Shave Club and The Trunk Club are very similar in that they provide a level of convenience to the customer. They both target men. The difference between the two is that The Dollar Shave Club aims to provide a cheaper shave while the The Trunk Club aims to provide designer clothing for a clientele who is not very cost concious.

The second business model we reviewed this week was novel way an eye wear company, Warby Parker sold both prescription eyewear and sunglasses for a lower price than traditional brick and mortar eye wear stores. The company had to over come the key obstacle where customers generally cannot tell simply by looking at the eye wear how they would look in it when they actually wore it. The company used its website to present hundreds of styles online and allowed the customer to pick 5 styles to try out. The customer could try out the 5 styles of glasses they picked in the comfort of their home and pick the one they like, Warby Parker would then order the prescription lenses made for the style of eye wear the customer picked. Interestingly Warby found it necessary to have a store front in a few markets to allow customers to visit and try out the styles. It was more of a marketing move rather than a revenue enhancing channel. Warby Parker's key to success is that they are able to sell chic eye wear for lower prices than your neighborhood eye wear store.

The third business model we reviewed this week was Hointer. The store was started by an Amazon.com executive and the logistic design of the stock room may have been leveraged from how amazon manages its stocks. The store incorporates smartphones into the shopping experience by requiring customer to download an app. The app allows the customer to simply scan the designs of jeans they like and order the size. When the customer is ready is try out the clothing the app initiates a backend robotic stock picker to have the clothes ready for the customer in the trial room. The beauty of this automation, is that it reduces the number of sales people on the shop floor. It also provides the customer convenience by having the customer pick the size on the app instead of wading through piles of clothes to find the right size.

The 3 business models discussed above have all been enabled by the Web 2.0 technologies. Automation and the ever present access to computing power and the internet will no doubt foster more novel business models. These models are designed to bring choices to the customer at low cost and  with high degree of convenience.

03 Week

Marketing is moving from customer segments to individuals. Seth Godin in his talk discusses the death of the TV industrial concept which informed us for the last 30 years. In a world where the customer has too many choices and very little time, all segment driven advertisements seems to be very similar and hence are ignored. Thus he argues that the advertisements have to be remarkable. In the past the marketer would target the majority of customers with their ads and that would bring them the sales. In this age of marketing, Seth argues that marketers should target the front tail of the  bell curve. He argues that markets should target the innovators and the first adoptors as these are the people who care and will spread the message through the rest of the customer base. These are the people who are passionate about their product domain. This concept was also referenced in the book "The Tipping Point," where Malcolm Gladwell discussed different types of people personalities who help spread a product message and make the product viral. Malcolm labelled these people as "Mavens". They were defined as experts in the product domain and sought out by other product users for their knowledge of the product.

The CEO of IBM Ginni Rometty informs that changes in technology and the ability to collect big data and make sense of it allows marketer to target individual vs. segments. She argues that the challenge is now in understanding data vs. gathering data. She see increased cooperation between CMO and CIO in the coming months where CMO will collaborate with the CIOs to discuss how to mine big data to gain a specific edge in marketing to a company's customer base.

Gill Frisbie and Frank Acito discuss "The long tail." The concept of the "The long tail" states that in a company that offers a vast selection of a product it will be able to sell up to 98% of that selection as it will have products that will cater to a customer's individualized tastes. The concept of The long Tail is similar to what Seth Godin discusses in his lecture, where he is advocating targeting customers on the fringes who are passionate about a product to spread the word about the product. The long tail theory states that there will always be "Mavins" or first adopters who are so passionate about their products that after they try what the masses have recommended they will continue to try and comment on products that are less well know within their domain. Gill and Frank both discuss some of the negatives of this theory in their lectures. A key point they make is that for retailers targeting the end customers it may make sense to hold a vast variety of items but for manufacturers, it make not make sense to produce items that are in demand by such a small specialized section of the population. Sure there will be some items that in a selection that will be hidden gems but there is a reason why most items in a selection have little demand. The reason is that they may not be as good as the more popular items.

The HBR article on social media discusses the creation of online communities which are very easy to form, to discuss specific interests. These communities allow for information dispersion within the community at an unprecedented speed. Marketer have to consider these communities to spread the product message to be successful in the current environment. Communities now form around interests and enthusiasts. The exact people Seth Godin suggests that marketers should target, as they are willing to listen and are more passionate about the products. It is key for today's companies to formulate a strategy to interact with these online communities for both the promotion of its brand and products but also to mitigate negative consequences and foster a positive brand image.

The paradigm shift in marketing channels and who and how a company should market has changed significantly over the last few years (I dare say months!). Technology has enabled this unprecedented velocity of change. Companies that hope to compete and win need to embrace the virtual social environment that are created by online communities. They have to be able to comprehend the vast amount of customer data to advise their marketing strategy to be streamlined to individuals instead of segments and finally they have to focus their marketing on customers who will listen; customers who are passionate about their interests and are willing to try new products. Companies who can keep up with the change in this marketing landscape will realize that marketing has become economically cheaper in this new age, but more complicated as the customer have the ability to express their opinions to punish companies that fumble in its marketing, product and customer service. On the other hand those same customers will exercise that voice to reward companies that listen and respond to their needs.

02 Week

As a follow on to last week's blog on crowd sourcing, I am going to reflect on how companies can go about using the data from crowd sourcing. I will also discuss the new paradigm of marketing created by the need for customers to express their opinions and be catered to on their terms.

First let us look at what we can do with crowd sourcing. In the 45 mins video by Alma Whitten on 'Lessons from Googles Approach to Internet Security, Privacy and Encryption' we learned how Google is harnessing the power of crowd sourcing to provide better results for searches. Prior to watching this video, I was naive enough to think that Google only has a special algorithm to rank the search results based on links to the pages. I was impressed to find out that there is more to it than just ranking based on linked paged. The ranking based on linked pages is only the first step, Google is also gathering and tracking how the user interact with its search results to create a story which it then uses to further refine its' results. The aggregation of millions of search result stories helps Google refine its' search accuracy while preventing deceptive websites "the bad guys" from manipulating its' algorithms. Second, Google is using its' vast knowledge of searches to combine with other sources of information to provide faster/real time modeling of trends. They have partnered with the CDC to see show how flu is spreading across the US in real time. Once again Google is using anonymous information provided by the crowds to create macro patterns that help the crowds and in this case the CDC to help monitor and control the spread of a virus. Google also uses the search data that the users enter to create stories to help with spelling correction and translation. Once again the stories created by Google search users and interpreted by Google on how the crowds behave is used to help the crowds achieve the results they desire.

In addition to using the crowd sourced data generated by searches through its' search engine, Google is at the forefront on allowing the user community to try out its' products and gain feedback to make it better. A recent example of this effort is Google Glass. Google released, Google Glass as a beta version to test the market. On its' Google Glass website it monitored how the customers were responding to the product and then it decided to go into full production with the device. Google also bought YouTube a few years ago. Once again, it anticipated that video production was becoming easier through new technology and it understood the desire of people to create and post their own videos. Google also realized that the trend to consume video entertainment was changing as well, from traditionally produced professional TV shows to videos created by the people, for the people, of the people.. the democratization of video production and consumption. A new wave of marketing was emerging which had swung from broad segment based marketing to very focused marketing and now to group based marketing. Google through its' platforms for blooging, youtube, gmail and search has been very effective en-chasing from this new trend in marketing.

Marketing today is not about controling the message. The best marketing strategies involve the customers in a conversation about the products and services. This marketing requires companies to trust their offerings and forces them to listen to their customers. Companies that make a half attempt at it or try to rig the results on the customer feedback get punishe, and the brand value takes a hit as evidenced by Ford's experiment with the "fordboldmoves.com." Technology has enabled the crowd to express their opinion and it cannot be stopped. If the crowd perceives manipulation, it reacts to further show it strength of opinion as evidenced with Diggs.com removal of the HD DVD encryption key. Successful companies have relinquished control of the message and have joined the wave instead of fighting it. These companies have built trust and are rewarded by customer loyalty. Further because of their openness to customer feedback they have been able to evolve their products and services to the exact specifications of the customer. As this digital marketing revolution proceeds, customers will continue to demand, at an increasing rate, exactly what they want, how they want it and when they want it. Marketing is a good thing for when the customer gets what he/she wants, when he/she wants it, without having to go searching for it.

Crowdsourcing has a few draws back as well. As Google found out, it can be rigged. Also, there is a tendency of group think that can have undesired outcomes. As the research presented in the "Star Search" podcast, it seems like there was tendency for customers to give extremely positive reviews for the most mundane items. Perhaps because of the tendency for people to feel that they are experts and that their decision is generally right. An interesting experiment was conducted by yours truly a few years ago. I had noticed a retail store with 2 exit/entry doors right next to each other. I had also noticed that the customers were only using one of the doors and almost no one used the other door. This was further perplexing because the number of people entering and leaving the store during a Sale was so high that people had to wait in line to leave the store. For a moment I thought, perhaps like others, that the other door was locked and I waited in line to exit the door. After a brief moment I realized the stupidity of this wait and walked to the other door and opened it and walked out. Once I did that I noticed that more and more people realized this and started to use the other door as well until there was an even distribution of people using both doors. In an other experiment, I decided to stand on a busy street for a few minutes staring at the top of a building with a perplexed look. I was not really staring at anything in particular, I was just wondering if I could get a following of people who would stand next to me and stare at nothing to try to figure out what I was doing. My experiment worked, within 5 minutes I had approximately 45-50 people standing next to me staring into nothing at a building the more a crowd formed the more people got interested in the crowd. I left the crowd to stand in the back and observe the phenomenon. It took another 10 minutes for the crowd to realize that there was really nothing and no one really knew why they were staring at the top of the building. People where just doing what others were doing. Both these experiments tell me that while crowdsourcing is the future and is powerful tool, it can go awry. It can provide meaningless information and can be rigged. Thankfully more often than not, crowdsourcing does provide information that is relevant and the best answer to a problem.

I find this subject very intriguing and I wonder what other experiments we can do that can better help us tweak the results of crowdsourcing so that incorrect or irrelevant information from the crowds can be detected and discarded. I am sure we will find an answer to this problem (if it is not already found) in the very near term, as the new wave of marketing, and innovation relies so heavily on this.

01 Week

Hi All,

Though I am regular reader of several blogs, this is the first time I am creating one. I had considered starting a blog a year ago but life got busy and I didn't get around to doing it. I am thankful that my Digital Marketing class at Kelley has required me to start this blog.

When I registered for this class I didn't know what to expect from it. But reading some of the week 1 and 2's assignments has  rekindled an interest I had in the subject of alternative business models. A few years ago I had read a few interesting books, "The Wisdom of Crowds" by James Surowiecki and "Tipping Point" by Malcolm Galdwell. I noticed some of the concepts we discuss in the first couple of weeks in this course are very closely related to these books. The concept of influencing your target customers by engaging them into your product/service design can make your products go viral was indirectly mention in the The Tipping point. The model of crowd sourcing was mentioned in The Wisdom of Crowds.

Crowd sourcing has been gaining traction at an accelerated pace in the last few years.  In addition to the examples mentioned in the reading for week 2, I have noticed that sites like "TaskRabbit.com" have provided market place for multiple people to request and fulfill tasks. I have noticed over the last few years, that business models that encourage a social gathering of like minded people to exchange information or request help have done exceedingly well. An other great example is a Project Management, Coding and QA platform business model developed by "www.topcoder.com" This company charges a client a yearly membership fee. It provides a platform where a client can upload specs and then freelance project managers and coders will bid on the specs with their proposed design and charge. Once again, this is a good example of a company that has built a platform that creates a market place. The clients get a view of different design solutions to their proposed problem and the client gets to chose the best solution at the best price. These market places have demolished the national borders and have created a virtual society based on meritocracy.

I have not been familiar with the marketing domain in general and I have to admit I have been slow to embrace social networks such as Facebook, Twitter, Flickr, google+ etc. I have been very concerned about privacy and how much information I would like to put out on the web where I don't have any control of who is seeing me and what companies are doing with  that information.  But, with the popularity of these networks, I am well aware that I am in a significant minority. With the world moving in the direction where people want to share their every thought with the world, clearly it is a gold mine for Marketers. People profiles can be fine tuned to an individual. Marketing can now be targeted specifically to a person based on his online habits and posts. I believe we have just scratched the surface up to now. Newer devices coupled with the treasure trove of information help companies not only target individuals based on what they want but also when they would want it. Technology is enabling a pace of innovation in this field like never before. From where we stand today, companies that want to succeed in this new technologically enabled world, will not only have to keep a pulse on business models that would threaten their existing business model, but also on how they plan to reach their customers to keep growing more by selling more effectively to people who are interested in buying.

Ladies and gentlemen we have front row seats in witnessing a rate of change in lifestyle, never seen in the history of human kind before.