Could Wave Be a Tsunami for Data Visualization?


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This week at Dreamforce 2014 announced its new cloud analytics platform, Wave. Wave is in part a byproduct of the June 2013 acquisition of the analytics startup EdgeSpring for an undisclosed amount. I see the acquisition is far more than another me-too business intelligence offering that, at first glance, might even seem a little late to the game. This announcement stands out not because of features or capabilities (which are, frankly, pretty cool) but because of what these capabilities could mean inside the customer community. It was interesting to get first impressions from colleagues, partners, and even competitors in the days following the announcement. If I had to summarize those in one sentence, it would be this: “Uh, I haven’t spent much time on what it is, but it seems pretty cool.” This Market Insight will explore the Salesforce Cloud Analytics Wave announcement – what it means, why it’s important, and the opportunity for

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What is the Cloud Analytics Wave platform?

Wave came to Salesforce in 2013 through the acquisition of a startup called EdgeSpring, which was founded in 2010 and had about $11 million in funding under its belt. EdgeSpring was outwardly focused on solving the surprisingly difficult challenge of making enterprise analytics scalable, which remains somewhat elusive for many organizations, despite substantial investments in BI over the last two decades. According to the 2014 Gleanster Business Intelligence Gleansight survey, the average enterprise organization supports three or more Business Intelligence solutions. Yet the number one reason for continued investments in BI is demand for data-driven decisions from executives and line-of-business workers. That’s a problem, because today’s most robust BI technologies are very capable, but the data isn’t all that accessible for the folks making the decisions.

EdgeSpring and many other startups are tackling this problem from a different angle with a new set of technological innovations. Today, in-memory computing, caching, and HTML5 are transforming the delivery of big data analytics across a variety of interfaces (desktop, tablets, and smartphones). The charts are sexy, fun, animated – and, most importantly, the analysis and rendering is wicked fast. EdgeSpring established a dozen or so partnerships with partners like Demandbase, DocuSign, AppSense, Lithium, and Xactly before being acquired. Further support for their level of innovation and natural alignment with

EdgeSpring is one of probably 40-60 vendors trying to solve data visualization issues in the age of big data. That includes startups and well established BI players alike. In some respects EdgeSpring sort of had the same effect the Apple iPod had on the industry when it launched years after the first MP3 player hit the market. It turns out that if you dial down the complexity and make a product do a few things really well, it’s massively scalable for people to adopt. Not every user needs to answer sophisticated data problems with deep ad hoc reporting tools. So when we talk about BI self-service and data visualization, you don’t solve it with robust BI at scale. In reality, the bigger challenge for enterprises is just providing basic business-level information about day-to-day operations in a scalable way.

Dreamforce 2014 WAVE Announcement

In two short years Salesforce combined core EdgeSpring capabilities with native value propositions inside the Salesforce1 platform, delivering a very cool data analytics tool in a massively scalable, collaborative, cloud-based infrastructure. And so a new sub-cloud was born in the Salesforce1 stack: analytics. And it gave birth to the Salesforce Wave platform. Or, wait; the platform is the Wave, but the analytics are in the cloud and all of it is on Salesforce1. Okay, so the positioning needs a little polishing or fewer names that mean the same thing. If you were confused, so were we.

What does Wave, the Salesforce analytics cloud, offer?

  • An analytics platform designed for business users
  • Cloud-based access to data from any source – from inside, apps, and mobile apps
  • Mobile and collaborative access to data
  • An intuitive user interface to customize dashboards and reports
  • Searchable access to data layers and attributes
  • Visually intuitive figures and animated charts
  • The ability to render the same data set in a variety of different charts or figures in real time
  • User-based collaboration and annotations on charts
  • Access to structured and unstructured data in dashboards
  • Workflow, alerts, and triggers
  • Device-agnostic views
  • Built-in Airplay to push dashboards on televisions and monitors (from a mobile device)

Is this a BI play for Yes and no.

Wave is not a replacement for more robust BI offerings from competitors like SAP, Oracle, IBM, and SAS. But that’s also what makes it unique for Salesforce top-line growth. To a certain extent Wave solves a different problem traditional players have struggled with. How do you make it easier to unlock operational data and allow users to intuitively interact with that data? We aren’t talking deep ad hoc analysis, just basic operational insights that churn the internal hamster wheels inside the organization. These are the kinds of insights that generally help everyone make informed decisions at scale. The scalability and simplicity of the offering makes Wave a short-list option for checking the data visualization box for the enterprise – especially for customers using apps or CRM.

But let’s be honest:’s biggest wart is how difficult it is to actually get data out of the system or report on the data in the system with native analytical capabilities. So if you buy into the vision for Salesforce1 or the power of building custom apps with, then Wave should be an exciting offering. Initial pricing for the Wave service will be $125/m per user for “explorers” who just need access to the data and $250/m per user for “builders” who import data sets into the system.

At these prices, the minimum an organization will spend is $5,000 a year (on 2 users), but that’s really not maximizing the value of the service. With per-user per-month pricing at these levels Wave may only be accessible to mid-to-large organizations – and because Wave isn’t a replacement for traditional BI investments, now we’re talking net new budget.

Will the Wave actually crest?

I have no doubt will trip over the 10% of current customers who will go all-in on Salesforce 1 and Wave – particularly big name brands that tell a wonderful story at Dreamforce events. To me this was a very exciting offering because Wave has the potential to instantly open up intuitive and fast analytics, dashboards, and visualization at scale for over 2 million Salesforce subscribers. But this pricing will cause many buyers to think twice, and may render the solution inaccessible to small-and-midsize buyers who may find these capabilities extremely valuable and far more accessible than native reporting in Even in the enterprise, tough decisions will need to be made about who has access to Wave at $125/m per user. That’s $300k a year for a sales team with 200 explorer licenses. The thing is that any time a customer can derive value from analytics, they make better decisions inside of the platform and Salesforce customers are more successful, loyal, and happy. That helps establish a stronger foothold within existing mid-to-large customers who may be more likely to invest in the larger Salesforce1 vision such as ancillary investments in marketing, sales, service, and community. I initially saw Wave as a way to manage loyalty and churn – sacrifice some margin on the BI opportunity to solidify the value of the platform.
The problem is, CRM is actually a very powerful offering and the vast majority of revenue comes from subscriptions to this product. But reporting and analytics leave much to be desired in the core product, making Wave an even more attractive option for most subscribers. Oh, this Ferrari? Yeah, it costs this much… and by the way, the steering wheel is extra.

That said, the data that is capturing is still massively valuable (whether it’s in a custom app or any of the Salesforce1 portfolio of products), particularly if it’s augmented and scrubbed. Salesforce captures mission-critical data for their customers, and their customers want to report off that data, which makes Wave all the more compelling. A fully integrated platform (with Wave capabilities) is truly a unique value proposition. I’m sure that was part of the conversation on the pricing. Think about what it would take to derive this kind of value and then price it a bit lower. The question is, are there enough enterprise buyers lining up making multi-million dollar investments in data visualization to make Salesforce a viable alternative instead? Oh, by the way, it’s multi-million dollar investments every year in a SaaS model. More than likely this is an offering that has to be championed internally and sold strategically by Salesforce. Sadly, I fear this approach may take a lot of wind out of its sails.

Beyond the very compelling value proposition behind the Analytics Cloud, there are four significant challenges customers will face, and all of these will give them pause before investing significant money rolling out Wave for internal users.

1. Users may not be ready.

Despite the volume of vendors that are trying to solve the “enterprise analytics” problem, nobody has completely cracked the nut yet. Analytics are either too complex or too expensive. That means that for the most part the users that Wave targets will take some coaching and prodding to actually open up to the power of self-service analytics and dashboards. That means money invested for less than ideal returns – at least initially. That said, there’s still tremendous power in just pushing standardized dashboards to these users via Wave and giving them basic operational insights they wouldn’t otherwise have access to.

2. The value of analytics decisions is still heavily dependent on the expertise of the user.

No matter how cool or robust reporting and analytics are, someone has to look at that number and make a decision that hopefully helps optimize the business in some way. Ideally those decisions need to result in higher return on investment for the business than the cost of delivering the insights.

3. Availability of data.

It’s really easy to say “you can plug in any data source in the cloud.” It’s a whole different ballgame to do it. Often the biggest hurdles facing analytics initiatives are data quality, data governance considerations, and a process for supporting a unique record identifier on customers to tie all the data together. In the enterprise we generally find that’s a half-baked internal capability. Some operational systems (usually the newer ones) follow robust metadata standards and data taxonomy standards. But more often than not, IT may not be comfortable plugging in legacy IT systems because it creates more questions than answers from users who constantly want to verify what they are looking at.

4. Context is very hard to automate.

For non-technical folks, when you think about data that is internally available for you, the easiest way to think about it is as rows and columns on a spreadsheet. Rows are records (think about a list of customers and all the data you have on them). You might have 10 customers or 10 million. What Wave and other systems basically do is derive top-level insights by aggregating rows and looking for differences: how many customers live in this city, how many customers paid over $500, how many of this product do we have in inventory, etc. It’s a simple way to aggregate the data. But Wave can take it a step further by analyzing relationships between columns. A far more interesting level of insight comes from analyzing the relationships between columns (your top row headers on the spreadsheet). Wave provides a very intuitive and basic way for business users to derive both types of insights. The challenge is knowing which available data is appropriate to analyze and compare. While Wave includes some very cool search capabilities for users to look for data attributes in the system, it doesn’t help users uncover relationships in the data attributes (the columns). That’s something that will surely be layered into Wave in the future, but for now it remains a significant hurdle to the average user gaining access to data. All this really means is that Wave is less likely to be used for drilling and ad hoc reporting for the average user – it’s really a customizable dashboard for operational key performance indicators, which is still cool. But will buyers pony up the cash to check that box?

Final thoughts

Cloud analytics is indeed an exciting offering and a much needed capability in the portfolio. At present, pricing is largely targeting upper Enterprise organizations that will still need to make a business case in addition to (not instead of) existing BI investments. Wave is unique, compelling, and innovative in its simplicity. Bottom line, the battle for the customer engagement platform will largely be won by deriving insights from data, not just capturing the data. One could argue that in some respects CRM is still largely a glorified data capture mechanism for most organizations. But as soon as we start to see out-of-the-box features from providers like that analyze win-loss data and uncover trends or ideal target audiences that users never even considered, things will REALLY get interesting in the analytics story. Wave is a phenomenal move for, but it has the power to be so much more if executed appropriately. It could literally transform the way organizations collaborate and disseminate analytics and help establish an advantage over competitors like Oracle and SAP. We hope the company doesn’t lose momentum as they champion the product, because it’s not just an issue for Enterprise organizations, but it’s got to be more accessible from a price perspective for to benefit in the long run.

Republished with author's permission from original post.

Ian Michiels
Ian Michiels is a Principal & CEO at Gleanster Research, a globally known IT Market Research firm covering marketing, sales, voice of the customer, and BI. Michiels is a seasoned analyst, consultant, and speaker responsible for over 350 published analyst reports. He maintains ongoing relationships with hundreds of software executives each year and surveys tens of thousands of industry professionals to keep a finger on the pulse of the market. Michiels has also worked with some of the world's biggest brands including Nike, Sears Holdings, Wells Fargo, Franklin Templeton, and Ceasars.


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