DotData is an early-stage startup in the artificial intelligence space, also known as AI.

“Well, it depends on the audience,” explains VP of Marketing Walter Paliska. “From a marketing perspective, the audiences we talk to have radically different sets of needs and depth of skills.”

Business Intelligence Professionals and Data Scientists.

Business Intelligence Professionals are technically knowledgeable, but not about AI and machine learning, he explains. So, that’s the BI or business intelligence world.

“They know the world of data. They’re very comfortable with data. They’re very knowledgeable as far as data and dashboarding and reporting is concerned, but they don’t necessarily have the data science background to be able to build the predictive models that are at the heart of AI and machine learning- the foundation of predictive analytics,” Walter notes

At the complete opposite end of the spectrum, are the data scientists who do this for a living. They often hand-code the AI and machine learning models; and the value proposition is fairly different for each.

On the one hand, the business intelligence folks, their value proposition is very much a no-code, end-to-end automation solution.

Basically you plug dotData directly into your source data, then dotData does its magic and AI machine learning models come out the other end that you can then choose to deploy onto your dashboards for predictive analytics. This is obviously a gross oversimplification, but this is the basic gist of dotData.

“For data scientists that’s not a viable option because of two reasons. Number one is the ecosystem, the tool set that data scientists use is much different,” Walter explains. “They’re heavy users of Python and scripting languages. So, that’s the world they like to live in. It’s very difficult to get a data scientist to move from that world and go to a point-and-click type of approach.”

And the second and probably bigger difference is that in the world of data science, data scientists, the challenge that they have, isn’t so much one of not knowing how to do the work, obviously: The challenge that they often have is this vast repository of data that they need to use in order to build their AI models.

“So, then the data scientist takes their features that they’ve developed manually, they combine them with DotData, and they can create richer models that have more features, that are better at doing what they do, they are more predictive,” he says.

DotData serves two main audiences: business intelligence, and data scientists. Both audiences use dotData in very different ways.

• For business intelligence professionals, it’s all about helping folks who are very skilled with data – but not necessarily with data science – in building the AI and ML models they need to create predictive analytics solutions – all with a turnkey no-code solution.
• Data scientists, meanwhile, need a way to enhance the work they are already doing, by finding previously unknown patterns in data automatically so they can build better feature tables. They use dotData to create models that are richer and more predictive, without labor-intensive hours of organizing and analyzing massive data sets.

For dotData, it was a two-fold challenge that brought them to Smashdeck. Being on fixed budgets and funded capital, all startups have to make a choice about where and how to spend, wisely. Oftentimes startups have small, scrappy marketing teams of one to two experts versus a wide swath of specialists.

“I don’t have a team of 20 people working for me. I don’t have an email marketing team and five content writers and four product marketers and so on,” Walter notes.

“So, what that means is that it’s very challenging for us to use a traditional top of the funnel approach thatgenerates a lot of low interest leads, and then nurture them down the funnel until they’re ready to talk to sales.”

DotData, armed with only a handful of marketers,, didn’t have the bandwidth to execute large-scale lead generation campaigns or paid acquisition.

From a lead generation perspective and to be agile, dotData decided in 2018 to focus on conferences, and events because they wanted bottom-of-funnel leads. This was working well until the world had different plans and Covid-19 morphed in-person events into a virtual model.

“We experimented with digital events but we really found that digital events were not as good as in-person ones from a lead gen perspective. Great way to get a lot of audience, but there were really more branding exercises than a lead gen exercise. So we decided, okay, we need to double down on the Sales Development Representative (SDR) effort,” Walter explains.

“We had an existing SDR partnership and they were doing a great job for us, but we wanted to try something new, something different. After a little bit of searching on the Internet, we found Smashdeck. What really caught my eye was the fact they use a Cold-Call 2.0 Approach,” Walter goes on to note.

Smashdeck doesn’t just call 10,000 people a month. Its approach is more about augmenting electronic communications to try and figure out the “hand raisers,” and then get the SDRs to call the ones that have expressed some level of interest.

dotData

“And that seemed attractive to us as a different way of doing things because we’re big believers in A/B testing to see which one does better. So, that’s kind of how we started with Smashdeck, and why we wanted to go down the path of expanding our Sales Development Rep Program.”

Since switching their pure SDR approach and signing on with Smashdeck, dotData has multiplied the number of leads generated through outbound SDR only, by about a little bit more than 10 X on a quarterly basis.

“The second big metric that I look at from an SDR perspective is lead quality and the way we measure lead quality is a multiple step process…”

1. Meeting Booked Form: Step one is dotData has a book-a-meeting form that someone fills out on its website that submits the lead.
2. Accept, Reject or No-Show: One of dotData’s lead stages is flagged, “meeting missed.” So, if a sales person goes on the Zoom call, and the prospect doesn’t show up, they flag it as “meeting missed.”
3. Qualified, Opportunity or Disqualified If the meeting finally happens, then the sales person does something with that lead, the lead becomes an opportunity, or it goes into further sales qualification, or it gets thrown into nurturing.
4. Lead Quality: When any of those events happen, automatically a Salesforce automation flags the lead as “meeting held.” Dotdata then measures what percentage of bookings on a monthly and quarterly basis that are booked actually happen.

“And again, the numbers for Smashdeck are outstanding. The people tend to show up. It’s as simple as that,” Walter says.

“The other big measurement that we look at is, what percentage of my pipeline has been generated by specific SDRs. And again, I don’t want to get into specific details, but the Smashdeck team has been great at generating a pipeline for us, a significant number of our pipeline opportunities come from Smashdeck.”