Acquire & AnalyzeBig Data
Your Presenters Curt Raffi - Host Jeff Kaplan - THINKstrategies Jason Mondanaro – MetraTech, Corp.
Acquire, Analyze, Act - A3           Making good decisions            requires information.           “Compute as you go...
Big Data - Been Happening All            Along   Financial Services   Risk, fraud, customer analytics   Transportation   M...
Big Data Sources     100%      90%      80%      70%      60%      50%      40%      30%      20%      10%       0%Source:...
You Are What You Measure Business is complex but pressure is focused on  single key metrics   MRR and ARPU Temptation i...
Obstacles of Our Own Design Subscription Cliff             Premium Plan   MRR models require    customers to make huge  ...
Share of Wallet Conundrum MRR means that you are competing  with everyone for Share of wallet.         +           != Tr...
Data Without Common Sense           Don’t make a bad            situation worse…
Making Advances, Growing theBiz Ramping Product  Models   Give the consumer an    easy path to increase    their busines...
You’ll Need Fat Data  Subscription : dumb data         Consumption : fat data
Shift Towards ConsumptiveDataNo limit                    Tiered                            Smart Grid                     ...
The Customer as a God
Wrap UpBuild your                                  Leverage        Use             Architect to   Visual turnsbusiness    ...
Last Webinar August 22  Act on pricing &   product strategies  out of the billing system to drive  more revenue
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Beyond Subscriptions and Monthly Recurring Revenue

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As more software companies become service providers by moving to the cloud, many are realizing that they need to change more than just their product models. Revenue models must shift, too. The old, gold standard of monthly recurring revenue (MRR) seems to be inherently anti-cloud. If software-as-a-service companies want to increase the profitability of their usage-based and subscription services, they must dig deeper into transaction-level data to get clearer insights into what users want and what they buy and plan for more elastic financials.

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  • In our first webinar in this series, Making Money with Big Data, we introduced the idea of Acquire, Analyze and Act or “A Cubed.”A3 Blah blah.Today we’re going to focus a little bit on Acquire and a lot on Analyze.
  • First I’d like to dispell a Big Data myth. Big Data is all about a volume of data that is hard to mange and use and people act as if this is a new thing. It isn’t. Many types of businesses have been generating far more data than can be managed with the technology at the time. Of course part of the challenge is that all this data is frequently being generated by different systems in different departments for very specific operational uses.
  • Another factor is the formatting of data sources. For everything a customer may do there are a number of Sub-transactional datasources that complement and inform the primary action. For example, prior to making a purchase a user might have watch some online video training, clicked through manuals and asked a question on a forum prior to making the purchase. All this information has traditionally been captured and part of the current revolution in Big Data is the improvement of the tools for parsing and cleaning this data.I often get asked by ISVs how to pass through their Azure or AWS charges to their customers. The problem is they have multi-tenant applications and do not capture consumption data into the Billing system. Sure they know what features people are using when, but this is not correlated with the service utilization and costs and therefore cannot be the basis of per customer operating margins and therefore feature based pricing to influence behavior and change margin. Many people are not charging based on the value their service offers at a granular level.Why?
  • Growing a business is tough. There are a lot of variables. The Rate at which you can acquire customers, the size of the addressable market, how much people are willing to spend and many others all influence each other. To summarize data into a quick and easy format we often resort to KPIs such as MRR or ARPU in order to gauge our progress. Pulling this data together can be tricky and sometimes the results aren’t good. So it is very easy for businesses to fall into the dumb-Data trap. For example, if you want to have an ARPU of $50 it is a lot easier to make your price a flat $50 Subscription! But What does that mean? It means you Limit your customer Acquisition opportunities to the people who think the Single Price is a good one. As soon as you pick a price you’ve limited your market. So then you decide to add more price point to get more addressable market.
  • A person with a budget of $20 cannot buy from two vendors with $15/month subscriptions. Somebody is going to lose and it’s probably you, the unknown relationship. You can try to add more features to entice new customers but think about how often bundles are perceived as negatives: PC Bloatware, Having to get a Sunroof and Mag wheels with your Bluetooth radio on a car package….How often do service providers schedule innovation on their roadmap that reduces costs and increases profitability without adding any new features?One of the original reasons for success by Asian manufacturers was a philosophy of identifying what price the consumers were willing to pay for a product and then innovating on the cost side to make that price point profitable. Often in software and services you see the exact opposite. People seem to come up with a price based on some internal metrics and margin commitments to investors or executives and then the scramble it to add more junk to the bundle to justify the price to the consumer.
  • I bet the people who came up with this price list made extensive use of Data analysis, they use algorithms to divide their customer base into segments and affinity groups and tried to make Package boundaries that maximized market segments. They’ve created a large number of “Subscriptions” I can guarantee that these are selected so that an overall ARPU is likely to be reached. It’s a lot of effort to come up with these tiers. But as a consumer I now have an overwhelming set of choices. If I think I’m going to be near a boundary I’m going to worry. But the reality is that all they are trying to communicate is that the more you use the less you’ll pay per unit….
  • If you want to influence behavior and how your services are used, you need to collect Big Data and use consumptive pricing models. If you don’t care what people do or set a generic one-size-fits-all service then simple Subscription is probably ok. Example Salesforce uses simple pricing but provides detailed limitations on service uses and volumes as a result.
  • Consumption Data is a key ingredient to building a business that minimizes obstacles but also becomes transparent and easy for a customer to understand.
  • Doc Searls claims that businessestreat customers as a herd of cattle to beowned. Information is provider centric based on a compulsory registration process or secret tracking. As the article says, it is like having a stalker taking note of your movements constantly. But the free data curtain call is a few acts away. Increasing consumer and privacy protection laws are going to increasingly limit the amount and type of information you can collect on a customer and more and more people are refusing to do business with websites that do not have a non-registration purchase path.People are going to demand that they be treated individually with negotiating power. They are not going to pay “List price.” They are going to want unique terms. Who do we know who behaves like this? Business Customers! So while we may have the Consumerization of Applications from a functional perspective we will see more and more individually negotiated relationships for the best customers regardless of their being individuals or corporations. The only way to make that scale is to have a firm grasp of your business, its margins and what can systems do to automate and empower these decisions.
  • Beyond Subscriptions and Monthly Recurring Revenue

    1. 1. Acquire & AnalyzeBig Data
    2. 2. Your Presenters Curt Raffi - Host Jeff Kaplan - THINKstrategies Jason Mondanaro – MetraTech, Corp.
    3. 3. Acquire, Analyze, Act - A3  Making good decisions requires information.  “Compute as you go.” Slowly scouring your data for insights 24X7  Integrate with billing tools that can provide analysis of your products, pricing & promotions.
    4. 4. Big Data - Been Happening All Along Financial Services Risk, fraud, customer analytics Transportation M2M, Internet of Things Telecom Customer profile monetization, revenue assurance Digital Media Real-time ad targeting, web analytics
    5. 5. Big Data Sources 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%Source: Aberdeen Group, January2012
    6. 6. You Are What You Measure Business is complex but pressure is focused on single key metrics  MRR and ARPU Temptation is to take the easy way out and guarantee the results.
    7. 7. Obstacles of Our Own Design Subscription Cliff Premium Plan  MRR models require customers to make huge decisions one time. If you lose the battle you don’t usually get to try again Basic Plan
    8. 8. Share of Wallet Conundrum MRR means that you are competing with everyone for Share of wallet. + != Trying to shift the demand curve by bundling has limits
    9. 9. Data Without Common Sense  Don’t make a bad situation worse…
    10. 10. Making Advances, Growing theBiz Ramping Product Models  Give the consumer an easy path to increase their business with you without making a decision  Arrange Valley’s of Comfort to delight Valleys customers, encourage Of Comfort ™ them to push a little Gentle Slopes more
    11. 11. You’ll Need Fat Data Subscription : dumb data Consumption : fat data
    12. 12. Shift Towards ConsumptiveDataNo limit Tiered Smart Grid GridCapex Cloud Fixed Market Price Pricing
    13. 13. The Customer as a God
    14. 14. Wrap UpBuild your Leverage Use Architect to Visual turnsbusiness cloud to pricing, rewa track user big data intowith scale out Big rds and activity and actionablemeasuremen Data offers – drive consumption knowledget in mind customer & partner behavior
    15. 15. Last Webinar August 22  Act on pricing & product strategies out of the billing system to drive more revenue
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