Salesforce Wave and the future of enterprise analytics

Profile picture for user pwainewright By Phil Wainewright March 7, 2016
Summary:
Analytics Cloud COO Stephanie Buscemi tells me about early traction for Salesforce Wave and what vendors must do to capture the enterprise analytics market

Stephanie Buscemi COO Analytics Salesforce at Dreamforce 2015 © Jakub Mosur Photography
Stephanie Buscemi at Dreamforce 2015

Ever since it was first announced in 2014, Salesforce has positioned its Wave analytics platform as one of its key product sets, intended to be an important revenue generator for the company. But it's seemed slow to gain traction, despite a slew of partner apps built on the platform, which debuted at last September's Dreamforce conference.

Last week, I met Stephanie Buscemi, COO of Analytics Cloud at Salesforce, for an update on Wave's progress. Buscemi has an eighteen-year track record in business intelligence and analytics, with roles at Hyperion, Business Objects and IHS under her belt before joining Salesforce in June last year.

Our conversation looked back over Wave's progress to date and also ahead to the future, not only in terms of new ease-of-use tools that Salesforce plans to add to the product, but also at what analytics vendors need to do to seize the initiative in this still-evolving market.

Critical milestone

Buscemi says that delivering the Sales Wave analytics app — Salesforce's own packaged application built on the Wave platform, and also the first to become publicly available — has been "a critical milestone." It became generally available last October.

It showed that the platform was app ready. For us to build apps on it, for ISVs, for developers within customers to build custom apps — if you think about, in eighteen months, it's a lot to do over an eighteen month period.

When we launched at first, we had the Wave platform and it was very much perceived as enterprise only, and a lot of that was due to things about a platform. Smaller companies want an out-of-box, packaged application. A platform can be a bit more daunting in terms of what it requires in terms of implementation, in terms of the price of entry.

[General availability of] the Sales Wave app, it's allowed us to very quickly, in our commercial business, go down market. We're not selling just the platform, we're aggressively also selling the analytic app, and that's really appealing to our small business and medium business customers, because it has a very conducive price point, it doesn't require a bunch of services, and it's a quick time to value on implementation.

In terms of a year and a half in, the app is being very well received. We also, right now, are in pilot for our Service Wave analytic app, we have a dozen plus customers in pilot right now.

Maturing the product

Salesforce still isn't releasing customer numbers, but Buscemi says the traction is there, especially helping sales teams to identify where best to focus their efforts, she says.

I can point to hundreds of customers who are really realizing the value of Wave through our direct selling right now. A large number of everything from Fortune 500 brands to smaller companies.

The most common selling motion we see is that the app starts as a departmental sale into sales, and it's a seed departmentally, and then a grow to the platform.

The product has matured too and that is also helping sales, she adds.

Over the last year, we have significantly matured the tooling and the product. We have created a much more declarative environment now — removing the need to do any code writing and making it a declarative, 'clicks not code' — huge advancements in that over the last year.

Being conscious that it was a V1 product when it first came out, I'm pretty proud of the maturing that we've done on the platform to make it easier for a business user or analyst, a non-technical individual, to render a dashboard and be able to interact with it and do the exploration.

Organizing data sources

That work to make the product more accessible to non-technical users will continue. One of the challenges with any analytics product is getting the right data into it in the first place. Salesforce — like many other vendors in the analytics space — is working on tools to make that task easier, she says.

Anyone can create a dashboard, but is it the right window into the data and information? Before you even are building those dashboards, before you're even looking at the consumption layer of whether it's on mobile or collaborative, it's all about, how do you ingest all these different data sources and then how do you organize the data? Making sure that you can transform and shape the data that it speaks to one another and that you have the data quality, the data lineage there. I would say that has elevated significantly within the world of analytics today.

We have a configuration tool built into the product today for Salesforce data that enables people to do some minor transformations and cleansing of the data and mapping of data to fields in the dashboard. Then we are [working on] a self-service data prep console in the Wave platform that will allow for the business user to do those same things easily in different data sources, and do some minor transformations around it.

Machine automation

The other main focus is on taking advantage of machine intelligence to automate elements of the analysis, so that the user has to do less work to figure out the answers they're looking for. Analytics isn't for everyone, she admits.

The reality is, not everyone is analytical and they're never going to be, it's like changing eye color for some.

I believe that we need to, 1) be conscious of that, and 2) that's where we bring in the prescriptive and the predictive analytics. Salespeople don't want to just look at the bubble chart. They want the next step, which is the prescriptive, 'Tell me what to do with those ten, twelve accounts,' or whatever number they're working on.

We right now are building those prescriptive models outside of Wave. We'll bring native integration for predictive into Wave, but we're very focused on very specific use cases, because I feel like predictive can be a bit overused, broad-brush stroke. To me, it's building predictive models for specific analytic use cases that are for sales, service and marketing.

The first one we're focused on right now is lead scoring. Rather than giving a rep a dashboard that shows them, not just 'I have this many leads or that,' but being able to give them 'Okay, here's the likelihood of each of these leads actually closing.'

That takes it a step further, and then we start to integrate natural language processing into that, to not only be able to give it them in a graph, but to be able to tell it back to them in text. For the non-analytic, we're going to need to go that far.

This is all part of building an analytics application that ultimately can become the front-end into other enterprise functionality, which Buscemi believes will determine the winning vendors in the next generation of enterprise software.

I actually think we will get to a place where analytics becomes the UI [user interface]. I'm looking at it where you're at the intersection point between the system of record — and you take those transactional processes and you now bring that together with the system of engagement, collaboration and a system of intelligence, which is the analytic app.

The system of record business is commodotizing out in the market, so I think whoever is fastest to market that builds the analytic insight — and that becomes the driving factor that dictates what happens in the business processes — and you enable collaboration within that, I think that will be the Trojan horse. I think that will be what makes people the winner.

My take

No quick wins here, but a big prize in the long haul for whoever figures out the best way to deliver enterprise analytics.