Editor’s note: This guest column is from Raj De Datta, the CEO and co-founder of BloomReach. Follow @BloomReachInc on Twitter.
With the influx of information flooding the web – 90% of the web having been created in the last two years alone – web businesses are looking for ways to understand and use big data to drive their business. Just as SaaS and the cloud completely revolutionized the way businesses operate, so will Big Data applications (BDAs). BDAs are web-based applications that interpret and use massive amounts of enterprise and web-scale data to deliver more intelligent results for their subscribers. BDAs leverage the best of the cloud; they’re web-hosted, multi-tenant and use Hadoop, noSQL and a range of recommendation and machine learning technologies.
But the real question is – so what? So what if the underlying data structures use Hadoop or noSQL? No CEO of a major business gets excited about a value proposition around more scalable data structures. That’s where BDAs come in. BDAs don’t just repackage your data in a cool interface or offer productivity improvements in data scalability, they harness the world’s data to deliver you a better outcome – like more revenue.
SaaS was a different delivery model for enterprise software: available for immediate sign-up, it dramatically reduced integration costs, enabling try-before-buy, scalability and shared tenancy with meter-driven pricing. Salesforce.com started the cloud revolution by transforming the CRM industry and was quickly followed by the SaaS-ification of every category of enterprise software (Taleo/Successfactors for HR, Netsuite for ERP, Omniture for web analytics). SaaS both increased the market size for business software (by enabling mid-size companies to buy at a lower cost of entry) and delivering a better ROI for bigger businesses. But it did not do one important thing–it didn’t change the functional capabilities of the core application. Salesforce didn’t add CRM features for businesses vis-a-vis Siebel – it simply made it easier to adopt and cheaper to maintain.
Big data on the consumer side of software is well-understood – Google, Amazon.com, Facebook. In a recent keynote speech at Cebit, Amazon CTO Werner Vogels noted that when mistakes have been made, it’s because there isn’t enough data to back up a recommendation. All of these are applications that get stickier, smarter and more valuable as more users and data pour into their core engines. Now, we are seeing the beginning of enterprise BDAs, and they are the future:
- Linkedin (NASDAQ: LNKD) is a BDA for the recruiting/talent acquisition software market. LinkedIn doesn’t ask you to add your contacts in an isolated contact list, it networks those contacts, connecting users with users and recruiters with key competencies. Every user that joins LinkedIn adds a signal to the LinkedIn BDA stack, enabling the recruiter to harness all their millions of profiles, not just their individual silos. As a result, smaller, specialized recruiters are competing with the biggest executive search agencies with comparable reach.
- Bazaarvoice (NASDAQ: BV) is a BDA for social sharing. Bazaarvoice collects customer reviews from across the web, then powers multiple websites with that information. The traditional SaaS-based approach to this problem would simply have provided software to accept and publish reviews on individual sites. Instead, Bazaarvoice collects review data from across the web to make sure when you pull up a product on one of its customer websites, the right reviews are presented to you. Bazaarvoice gives all sellers comparable review databases to Amazon.com.
- Salesforce (NASDAQ: CRM) understands that BDAs are the future of SaaS. When it acquired social listening software company Radian6 and contacts company Jigsaw (now Data.com), Salesforce understood that the powerful application for brands would be aggregating social data points on brands from across the web and networked contact information to salespeople.
- Our business, BloomReach, is a BDA for marketing, the next $10bn category in software. We could have merely analyzed websites to identify missing relevant content that could drive revenue across search, social and advertising traffic and made workflow and content recommendations to site owners. Instead, we decided to analyze and interpret web-wide demand, build semantic models around web content for a given customer and then dynamically augment websites with the most relevant content for their users. Adobe’s Omniture packages your data in a cool SaaS application to make marketing recommendations for your business. BloomReach analyzes the web’s data and then acts on it to drive more traffic and revenue to our customers.
BDAs are inherently better than their SaaS equivalents because they have all the delivery model benefits of SaaS, plus a network effect in the data being collected. Unique data, put to work for each customer, is an asset that creates network effects over time for both subscribers and for the application provider. These days, there is so much more data outside the enterprise than within it, that the notion of re-packaging an enterprise’s own data for analysis and workflow seems quaint.
BDA companies create value differently than SaaS companies. BDA companies are built by teams of people with a strong background in large-scale systems and machine learning / data mining (like my co-founder Ashutosh Garg). They will also be valued differently than SaaS companies. While both sell into enterprises, BDAs deliver much more value per dollar spent, because each acquired customer adds data to the engine, which in turn improves the service for all its customers. Markets typically value SaaS companies on three basic metrics: Customer Lifetime Value (higher LTV is better), Cost of Customer Acquisition (lower CCA is better) and Rate of Growth (higher is better). Certainly, most SaaS companies have a great growth rate. But BDAs will have higher LTVs (because value/customer is higher and churn will be lower) and lower CCA (because of network effects; consider the CCA for LinkedIn to acquire a new recruiter now, versus five years ago).
The BDA revolution is just beginning. If we were building CRM again, we wouldn’t just track sales force productivity; we’d recommend how you’re doing versus your competitors based on data across the industry. If we were building marketing automation software (Marketo, Eloqua), we wouldn’t just capture and nurture leads generated by our clients, we’d find and attract more leads for them from across the web. If we were building a financial application, it wouldn’t just track the financials of your company, it would compare them to public filings in your category so you could benchmark yourself and act on best practices. Every category of software will have a BDA leader (some may be current SaaS companies that adapt or acquire).
Like anything in technology, the next new thing doesn’t mean the old things go away. Oracle and SAP are still big companies but Salesforce.com is the newest $20 billion behemoth. The new kids on the block will be BDAs.
Hello BDAs, Goodbye SaaS.
Originally posted here:
The Rise of Big Data Apps And The Fall of SaaS