Tell us about your role and the team/technology you handle at 250ok.

My role is primarily focused on defining the Product vision, its roadmap, and the strategic requirements to align our Product strategy with customers’ goals.

From conception through launch, I work closely with engineers, marketers, and stakeholders to define what we’re building and why we’re building it. It’s an incredibly rewarding mix of interfacing with customers, planning development sprints, coordinating pilot programs, and working with Business Leaders to assist in pricing, positioning, and creating compelling stories with data.

What powers 250ok’s Email Analytics’ data engine?

From a Product perspective: experience. We have a highly talented team with years in the industry at the likes of Salesforce, ExactTarget, Marketo, Adobe, and others. It’s our resident experts that transform customer data into tangible analytics stories which lead to better performance and better outcomes.

On the technical side, our analytics data engine is powered by a vast network of data. In large part, the email industry is broken down into niche, one-off components or features that are sold independently. As a platform, 250ok sees billions of data points ranging from a variety of products, including analytics, email list quality, sender reputation, and sensor networks. The list goes on, but because of our reach, the 250ok platform has the benefit of seeing data from every facet of email to allow our products to inform each other and provide a holistic picture of performance.

Do you leverage AI ML algorithms at 250ok? If yes, tell us more about your AI research and analytics.

250ok pays close attention to ML and AI trends, but first, it’s important to distinguish between ML/AI and routine business logic. Send time optimization, event-based transactional messages, and segmentation are based on historical data to power algorithms and workflows. They’re all Marketing activities commonly associated with ML/AI, but also activities rarely involving any form of ML/AI.

Since ML/AI inherently relies on automation, marketers are frequently challenged by Marketing platforms without the underlying APIs or infrastructure to support automation. And where automation isn’t supported, Marketing teams may not have the budget or resources to manually implement the outcomes into their MarTech stack.

With this in mind, 250ok’s Machine Learning efforts have focused on data analyses producing actionable outcomes for marketers. Analyzing recipient engagement history allows us to identify recipients at risk of disengagement, which then serves as a predictor of churn. By comparing list quality to list acquisition sources, we could reasonably predict how customers will perform based on where they were acquired, and in turn, improve ROI by improving the acquisition methods behind the worst performers. By looking at a customer’s mailing list composition, we can predict how they’ll be impacted by deliverability issues, reputation issues, etc.

There are many areas where Machine Learning can dramatically improve Email Marketing performance. If send time optimization is simply looking for patterns in open times, when does send frequency become a factor? How about form factors (i.e., device, mail client)? Is the content optimized for those devices?

Email as a whole is far from optimized, but our roadmap accounts for the existing landscape while asking important questions about how email is evolving.

What makes marketers lose focus from deliverability promises? What common misconceptions you see and hear from vendors and customers?

The first big hurdle for marketers is ease-of-use. Deliverability tools are historically difficult to use and are often focused on “here’s a problem,” but lack the “here’s how you solve it” part of the equation. That’s why 250ok is heavily focused on training algorithms to leverage our data to not only predict when there will be a problem but also guide our customers on how to solve it.

The second hurdle is around making false promises. Many prospective customers come to 250ok looking for a magic bullet, and the truth is deliverability is hard. That reality is why we’ve made concerted efforts to educate our customers, provide guidance on best practices, and correct misconceptions whenever we can.

If you take a step back, email as a communications medium is a complex puzzle of mixed pieces: email marketers, email service providers, mailbox providers/receivers, deliverability consultants, anti-spam organizations—it can be daunting for email marketers to know where to begin. It’s 250ok’s mission to serve as the starting point.

What are current trends in validation and what features should CMOs check before investing in Email List Validation platforms?

Innovation. Email List Validation platforms have largely operated the same over the years and there’s significant room for improvement.

250ok sees list validation shifting from passive to proactive, meaning list validation must evolve from an after-the-fact measure of purging bad data, to a proactive measure of improving quality data acquisition at its source. This is the difference between validation and verification: 250ok wants to see more verified subscribers contributing to the growth of email programs.

The second shift is going to be analytics. Traditional validation offerings do not offer much beyond “X addresses were collected and Y were invalid,” which leaves a big blindspot for marketers. 250ok is interested in attributing email addresses back to the channels by which they were acquired, and as a result, determining why an address was invalid in the first place. That is where list validation shifts from risk reduction to Marketing enablement, and post-collection address loss (validation) can shift to valid address growth (verification).

What is the current technology driving Data Analytics for MarTech platforms?

Primarily business logic. Although marketers have clung tightly to the buzzword value, meaningful advances in AI and Machine Learning are still in their infancy. Regardless, the path is being paved for much more compelling predictive analytics products across the MarTech stack.

Tell us about your Product roadmap for the next 2-3 years?

250ok’s roadmap for the next two to three years is heavily focused on data acquisition and predictive modeling. There are countless email service providers responsible for sending emails, many of which are our customers (e.g., Salesforce Marketing Cloud, Adobe Campaign/Marketo, HubSpot, Twillio/SendGrid, Acoustic—formerly IBM Marketing Cloud), so we’re building the business logic sitting in between senders and receivers to better serve the entire ecosystem.

Within the next few years, I envision 250ok integrated with all major platforms including email service providers, CRMs, analytics, and point of Sale vendors to overlap email activity with purchasing behavior, demographics, and Marketing activities that stem from outside the scope of email.

The second area of interest is prediction, which has many facets. For instance, years of historical deliverability insights should inform how your next campaign might perform. When we look at historical campaign engagement, we can reasonably predict which customers are at risk of disengaging. While some of this is included in our platform today, it’s only the tip of the iceberg, considering what’s coming soon.

The third area of interest is improving conversion and post-conversion outcomes. If we know why some Marketing activities perform better than others, or what patterns lead to disengagement, we can certainly make recommendations based on what’s tried and true. We’re developing new features targeting the entire email lifecycle: Data Quality at acquisition, Marketing Attribution post-acquisition, relevant communication to reduce churn, and quality list growth.

What are your predictions about Email deliverability analytics transforming Marketing and Sales in the next 3 years?

We definitely see mailbox providers heading in the direction of personalized experiences. The general idea is that mailboxes should shift from a single inbox view (list of emails in an account) to a more organized approach, such as categorizing emails by context. A great example of this would be grouping receipts or travel itineraries for recipients so they’re not having to dig around to find what they need.

The shift to contextualization will pose a challenge for Sales and Marketing in the next few years. Many MarTech stacks don’t have the underlying infrastructure to support things like Google AMP (interactive emails), Gmail Annotations (to display special offers), or define message metadata to inform mailbox providers on how their content should be categorized. Much like how web analytics inform targeting, which ads get served up, etc., email analytics must inform marketers on whether they’re hitting or missing their targets.

Additionally, email analytics can transform Marketing and Sales by getting more predictive; knowing what to send, whom to send it to, and when. Since Marketing promotions are still largely batch-and-blast, we see a ton of opportunity for more meaningful 1:1 communication. We see email analytics guiding marketers to messages that are more transactional in nature: personalized, contextual, and triggered by a specific action a recipient takes.