The Latest from the Go-to-Market Experts
April 25, 2019
An Inside Look at Oracle’s Account-Based Strategy
This post is based on a podcast with Steve Watt and Kelvin Gee. If you’d like to listen to more #FlipMyFunnel Podcast episodes, you can check them out here and listen to this episode below!
Ready for a account-based strategy treat? This week Steve Watt continues as a guest hont on this #TakeoverTuesday episode. He interviewed Kelvin Gee, Sr. Director of Modern Marketing Business Transformation.
With a title like that, you know this interview is going to be packed with insights into revolutionary account-based strategy and tactics.
Here’s what we’re unpacking today:
- Why hiding your weaknesses and accentuating your strengths is exactly what you should be doing
- What tools and platforms Kelvin is using for his account-based approach at Oracle
- Getting buy-in from all areas as you start an account-based strategy
- Rethinking your metrics from demand gen and MQLs, to targeted account metrics
- How Oracle is cutting through the noise
- How to avoid ABM mistakes and pitfalls
You often use a basketball story to illustrate the change going on at Oracle. Can you share that with us?
I usually share the story about Vivek Ranadivé. Vivek grew up in India. He came to the U.S. and earned his MBA at Harvard, and started a couple software companies, but he realized he wanted to bond with his daughter.
He knew little about sports except for soccer and cricket, but he started to coach his daughter’s middle school basketball team. As an outsider, he thought the game was strange because kids would just score the basket and retreat to their end of the basketball court, leaving two-thirds of the court undefended. He also knew the girls he inherited weren’t very athletic, couldn’t dribble, and couldn’t shoot. He knew if he played basketball the traditional way, his team would get soundly defeated.
He decided to play full-court press. He trained them differently, because if you play full-court press throughout the entire game, it’s exhausting. He didn’t train his girls to shoot or to dribble. He just trained them to run.
They started to beat these athletically gifted and superior teams with outrageous scores, 20 to nothing, 30 to nothing by half-time. Coaches would get frustrated and throw chairs in the middle of the basketball court or challenge him to a fight in the parking lot. They didn’t think he was teaching his girls how to play “proper basketball.” He maintained the course, and he ended in the national championship game that year.
I use that story to talk about how companies need to pivot and move to an account-based strategy and move away from traditional demand gen, because we all know the waterfall is broken and doesn’t work.
Here at Oracle we have our own set of challenges. In some ways we can’t dribble, we can’t shoot, we’re not as athletically gifted or nimble as some of our competitors. Vivek basically hid his teams’ weaknesses and accentuated their strengths, and that’s what we need to do at Oracle. We’re really good at outbound marketing. We’ve got tons of data, we’ve got organizational scale, we’ve got great relationships with customers. We have 420,000 customers, so if there’s one company that should do account-based and do it well, it’s us! That’s the moral of that story.
How did you go about beginning to lay those foundations to make that change?
Well it started with getting alignment, much like how Vivek got alignment with his girls and the buy-in on the strategy. We here in Oracle Marketing had to get in alignment, and that started two years ago when we rounded up the troops and had our first annual account-based summit. We had to align field marketing, corporate marketing, marketing operations, the analytics team, sales to a certain extent, product marketing … all the different silos that you typically see in a large organization like Oracle. We had to get buy-in that this is the right approach. Regardless of what we call it, we have to take an account-centric view versus a product-centric view.
Did you start with a small subset, such as 1 geographic area, 1 LOB?
Yes; We needed to prove that account-based at scale works, and we would implement support pilots around the world, primarily in North America, since we’re headquartered here. Then, we’d support that pilot by providing agents who support technical resources, budget support, and seeing which pilots work and which ones don’t, and learning and iterating from those mistakes.
Did you rethink some of your demand gen metrics when you were starting that pilot?
Yes. If you use traditional demand gen metrics to measure your account-based program, your numbers will look worse not better. You need a new yardstick to measure your account-based program. If your program is about building new pipe, you have to look at target accounts pipeline (TAP).
You have to look at account engagement or an account engagement score, which could include MQLs, but it also includes other things like: how are people interacting with your content? How are people coming to your website or consuming your blog or attending your events? You have to look at it holistically. It’s not just about MQLs.
Generally speaking, we are looking at engagement. We take a snapshot at a set of accounts before the program starts, then we take a snapshot after, and, hopefully, you should see a spike in the engagement. Then you also want to look at your pipeline. Take a snapshot before your program starts at what your pipeline looks like and then take a snapshot after. Hopefully, that pipeline would have grown.
Those are the 2 primary metrics we look at — engagement and target account pipeline — but there are other metrics we also advocate, like opportunity rate or how many accounts that you’ve targeted have net-new opportunities? For example: If you have 100 accounts you’re targeting and you have now 13 net-new opportunities you have an opportunity rate of 13%.
What are you doing to cut through the noise and build that engagement?
Personalization at scale is a really important factor. We have a framework here at Oracle. It’s a four-pillar framework:
- Target the right accounts, using predictive intelligence.
- Develop insights throughout those accounts so you can create content that resonates with them.
- Orchestration: So the right hand knows what the left hand is doing.
What are some of the tools or platforms you’re using for your account-based program?
Our predictive intelligence framework is built around three dimensions of data, fit, intent, and engagement, and we partner with some third-party vendors like a Bombora on intent side, like a Mintigo on the fit side. We also leverage our own first-party data and build internal propensity to buy models to determine who’s a good fit for us.
We also have our own topic score, taxonomy, so we can understand who’s engaging with our content on our own websites and web properties. Between fit, intent, and engagement, we can triangulate who’s a good fit and who’s searching, and who’s engaging, and we give the appropriate score.
Anything you would do differently if you could roll back the clock and start this journey all over again?
First off, that’s the great thing about account-based (or anything that you try or pilot): You constantly iterate. One thing we have learned: Maybe you should stage a re-launch based on your learning, or perhaps you have to be honest with yourself about what went wrong with a particular pilot and learn from that mistake.
We learned from one campaign that maybe leftover tchotchkes are the gifts that we would send out as direct mail. We could use it as bribes for our sales brethren to incent them for follow-ups. We just try to learn from each mistake and apply it to the next campaign.