Successful Business Models in an Age of Personalization filter out the noise generated from databases, sensors, and people, and provides filtered, data-driven, automated, relevant and actionable reports for people, teams and businesses so that they can better serve their customers and partners and other stakeholders. The trick is to digitize the information, engage and connect the communities of stakeholders, garner wisdom from the crowds as well as usage data, deputize contractors to deliver quality goods and services to-the-door, and continue to leverage Data, Sensor, Software, Network and Operational Advancements to sure that CUSTOMERS receive the personalized services they expect. Below are descriptions of these categories of business models and examples of companies implementing them well.
Monetizing Digitized Content connects creators, consumers, communities and sponsors. It’s remarkable what NetFlix has done in the movie industry, taking down companies like Blockbuster, and what Amazon has done for books, moving us to paying for digitized volumes.
- Progressive newspapers like the Wall Street Journal and the New York times are successfully selling online and mobile subscriptions to their targeted audiences. And businesses like Issuu work with tens of thousands of periodical publishers to convert print to digital formats, making it easy for publishers to do the conversion from print to digital.
- In the gaming and sports industries in particular, you will find that consumers are willing to pay more for quality, exclusive content. For example, ESPN is now partnering with local carriers to offer premium access to targeted sports content to their most loyal customers. And Sony Online Entertainment subscribers can pay $15 a month for select enhancements, including: more character slots and storage, 10% discount at SOE’s marketplace and a monthly allotment of virtual currency for purchasing upgrades.
Engaged Audiences and Communities will lead to more connections, more targeted conversations and longer and deeper interactions between members.
- Many of these niche communities will make it easier for advertisers to connect with their targeted prospects, and help community members receive relevant information and deals. In fact, advertising strategies will target relevant communities, and will no longer focus on the Web 2.0 eyeballs-and-exposure strategy, preferring Click-Through models, which benefit both the advertisers and the prospects/customers.
- There is strength in numbers, and a good example of how that’s working is in the Crowdfunding Connecting with others to jointly fund promising ventures is lower risk, with potential up-sides. This trend will amplify and extend in other ways as well.
Wisdom From the Crowds leads to empowered and informed consumption. Getting vetted, impartial recommendations from trusted and experienced networks will saves time and money and increases the likelihood that you will be happy with the product and the results.
- Product, Music and Service Recommendations: Whether it’s getting product recommendations with services such as Needle and Peerlyst, or getting music and playlist recommendations from your friends through iTunes or Spotify, or service recommendations through Angie’s List, Care and Thumbtack, it is very powerful and useful to get the input of the experts, people who have been-there, done-that, but without a motive or agenda. This crowd of experts-in-the-field and others with similar needs will continue to fuel purchasing decisions for all.
- Social networks such as FaceBook, LinkedIn, and Twitter help you connect with your network, communicate with your community, and create a platform to share your views. The crowd will help determine who’s popular, followed and respected – and those that are influence the decisions, thoughts and actions of others.
Post-Sales Data will help retailers proactively serve customers. Retailers are reasonably sophisticated today using past purchasing patterns to plan-fully stock their shops, but having data about what happens after purchases will help retailers even better prepare for and even anticipate customers’ preferences.
- Information on what happens *after* a product is brought home – whether it’s used, how often it is purchased, long-term data on buying patterns for that product – will help retailers better project and plan for anticipated needs for niche customers, regions, areas.
- The Next-Generation of Mail Order retailers will be data-based, of course, assuming preferences on styles, colors, costs, quantity etc for each niche market. But what will be different will be how proactively send products out to customers with minimal risks to those customers, and then how they take feedback from customers to progressively more personalize future offerings.
Deputizing Vetted Local Vendors and Providers will conveniently bring products and services to the door. It’s hard to build an army of providers to serve the personalized needs of specific people in specific areas, and even harder to scale that army. Here are examples of companies successfully doing so.
- The UBER/Lyft example shows how an army of deputized, local couriers will forever change the way people think about how to get from one place to another – and forever transform the taxi industry. Look also at what Surf Air is doing – providing all-you-can-fly memberships to-and-from convenient locations to frequent flyers. What will this mean to the airline industry in general?
- Amazon Fresh and Google Express are examples of how forward-thinking companies leverage technology to efficiently deliver perishables regularly to the doorstep. Both Google and Amazon will leverage supply chain concepts, delivery-optimization algorithms, and targeting populace target markets. Google Express will target the delivery of non-perishable staples, perhaps with the support of self-driving vehicles and Amazon Fresh will focus on efficiently delivering perishables. Both will continue to transform how we think about grocery shopping and online retailing.
This list isn’t intended to be exhaustive – in fact we will soon have a separate post that’s all about the data – filtering out the noise to find what’s relevant. Meanwhile, your input and thoughts are welcome.