Q&A with John A. Steinert, Chief Marketing Officer at TechTarget

John A. Steinert, Chief Marketing Officer at TechTarget helps bring the power of purchase intent-driven marketing and sales services to technology companies.

With a strong drive to help customers achieve their business objectives faster and bigger, John and his TechTarget team connects the information needs of enterprise tech buyers and the go-to-market efforts of solution providers, ensuring that everybody wins.

MEDIA 7: What inspired you to get into marketing?
JOHN STEINERT: 
That’s easy. Marketing inspired me to get into marketing. I’ve always loved great communicators and the formats used in communications. As a kid during some pretty tumultuous times in American history, I was surrounded by great political, guerilla, and yes even commercial communications. Speeches, hearings, demonstrations, TV, advertisements, even album covers and t-shirts made a strong impression on me. Obviously, with the rise of the internet, long-tail video channels and social media, things have blossomed to an even more amazing level.

M7: How does TechTarget's Priority Engine™ support tech vendors to achieve their marketing and sales objectives?
JS:
 By helping companies see and interpret real buyer needs and preferences, Priority Engine first provides a relevant, permissioned basis for a marketer to intercept a buyer’s journey and then it assists users in taking very specific influencing and engagement actions. Because Priority Engine provides the actual permissioned people doing buying research, it saves tons of resource that’s commonly wasted chasing prospects who don’t have a need and leads that are actually dead ends. And because Priority Engine shares the real needs and preferences of the actual buyers with both marketing and sales when they share the platform, it enables far better conversion at every step, from funnel, to pipeline, through to renewal.


"To truly enable sellers with content, the content needs to reflect what we know about this specific buyer’s needs and preferences."

M7: What according to you is content-enabled selling and how does it help drive a buyer’s journey?
JS: There are two key pieces to content-enabled selling. The first is the content itself – what it is and how it assists the buyers in fulfilling the necessary or required steps of their buying process. The second is how we adjust our own approach in response to buyer inputs and feedback.
To truly enable sellers with content, the content needs to reflect what we know about this specific buyer’s needs and preferences. To perform better, your content needs to be more buyer-centric. This can be achieved when product marketers and sales enablement folks are consuming real purchase intent insights from Priority Engine and leveraging them into evolved content outputs.

Then there’s what I’ll call the “personalization wrapper” – how the communications that accompany the assets present and create context for that use-case relevant material. These wrapper – be they email copy, call guides, etc. must be built with an eye to the nature and the stage of the relationship at hand. Marketers and sellers alike need guidance on the proper way to do this.

It’s not as simple as “you liked this so of course you should want to buy this”. Buyers need help with both their rational business needs and their more emotional needs around both their company, their department and themselves. The “personalization wrapper” is a useful metaphor for being holistically considerate of the person and the company you are interacting with. Obviously, this is substantially more nuanced than simply recognizing what company they are from. It’s about ingesting what you can see are their expressed concerns and preferences, learning from that, and shaping your own communication in that context.

M7: What features make TechTarget's 'Data-Driven Display' drive B2B demand and accelerate sales?
JS:
 Because it’s fueled by permissioned knowledge of exactly who is performing research at any given moment, TechTarget’s data-driven display advertising can deliver higher engagement rates and higher conversion.  When used in conjunction with demand generation techniques and intelligent sales outreach, independent studies with leading 3rd parties have achieved remarkable lift across the funnel as compared to what’s available when using more generalized “intent” data.


"The biggest mistake of all that’s commonly still made in marketing is to not use prospect behavior as a critical guide."

M7: What is the biggest mistake B2B marketers make while targeting specific prospects?
JS:
There are many actions that teams continue to take because they’ve simply been tasked to take them.  There are old-school KPIs, typically focused on process outputs rather than business outcomes that perpetuate chronic under-performance. Take, for instance, a narrow focus on cost-per-lead – too often this incentivizes continued purchases of higher and higher volumes of lower and lower quality. To wean themselves off of this Catch 22, teams should work to turn their attention to down-funnel metrics like conversion-to-opportunity – measuring cost per opportunity is a much more useful predictor of pipeline yield.

But the biggest mistake of all that’s commonly still made in marketing is to not use prospect behavior as a critical guide. When marketing (and sales) energies are spread evenly over active and inactive prospects alike, energy is wasted on those who are not in-market, and that investment of time and resource is not available to increase attention on those active buying teams that should be converted. By focusing more intently on those prospects that are actually demonstrating in-market buyer’s journey behaviors, teams get far more out of their investments.

M7: How does 'Data Cleanse' assist marketers in email verification and contact record accuracy?
JS: 
Some percentage of the data coming into your database from form fills, other manual entry and so on naturally contains incompleteness, mistakes and outright falsehoods. Furthermore, people move around, both inside of companies and between them. So even once-accurate data decays amazingly fast. To counter these realities, your data practice should put into place a variety of processes that together comprise a mature “data cleanse and append” approach. In this way, you can address data quality issues at both the point of entry and over time. At TechTarget, we offer our clients cleanse and append services both directly via our Oceanos offerings and indirectly via our Priority Engine platform wherein the data goes through rigorous checks and verifications before it qualifies to be shared.


"Even once-accurate data decays amazingly fast. To counter this reality, your data practice should put into place a variety of processes that together comprise a mature “data cleanse and append” approach."

M7: When did you start working, how old were you, and what was it?
JS:
 My first stable paid position, $1.40/hr, was at age 14 pumping gas at Greene’s Exxon. I was super excited because I got to wear the striped shirt with the logo patch! I loved washing windshields and checking the oil, especially when my superior CX delivery got me a few cents in tips!


ABOUT TECHTARGET

TechTarget (Nasdaq: TTGT) is the global leader in purchase intent-driven marketing and sales services that deliver business impact for enterprise technology companies. By creating abundant, high-quality editorial content across more than 140 highly targeted technology-specific websites, TechTarget attracts and nurtures communities of technology buyers researching their companies’ information technology needs. By understanding these buyers’ content consumption behaviors, TechTarget creates the purchase intent insights that fuel efficient and effective marketing and sales activities for clients around the world.
TechTarget has offices in Boston, London, Munich, Paris, San Francisco, Singapore and Sydney. For more information, visit techtarget.com and follow us on Twitter @TechTarget.

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PR Newswire | January 25, 2024

Cato Networks, the leader in SASE, announced the expansion of the Cato SASE Cloud platform into threat detection and incident response with Cato XDR, the world's first SASE-based, extended detection and response (XDR) solution. Available immediately, Cato XDR utilizes the functional and operational capabilities of the Cato SASE Cloud to overcome the protracted deployment times, limited data quality, and inadequate investigation and response experience too often associated with legacy XDR solutions. Cato also introduced Cato EPP, the first SASE-managed endpoint protection platform (EPP/EDR). Together, Cato XDR and Cato EPP mark the first expansion beyond the original SASE scope pioneered by Cato in 2016 and defined by industry analysts in 2019. SASE's security capabilities encompassed threat prevention and data protection in a common, easy-to-manage, and easy-to-adopt global platform. With today's announcement, Cato is expanding SASE into threat detection, incident response, and endpoint protection without compromising on the architectural elegance captured by the original SASE definition. "Cato SASE continues to be the antidote to security complexity," says Shlomo Kramer, CEO and co-founder of Cato Networks. "Today, we extend our one-of-a-kind SASE platform beyond threat prevention and into threat detection and response. Only Cato and our simple, automated, and elegant platform can streamline security this way." An early adopter of Cato XDR is Redner's Markets, an employee-owned supermarket chain headquartered in Reading, Pennsylvania, with 75 locations. Redner's Markets' vice president of IT and Infrastructure, Nick Hidalgo, said, "The Cato platform gave us better visibility, saved time on incident response, resolved application issues, and improved network performance ten-fold." (Read more about Redner's Markets and Cato in this blog. "The convergence of XDR and EPP into SASE is not just another product; it's a game-changer for the industry," said Art Nichols, CTO of Windstream Enterprise, a Cato partner. "The innovative integration of these capabilities brings together advanced threat detection, response capabilities, and endpoint security within a unified, cloud-native architecture—revolutionizing the way enterprises protect their networks and data against increasingly sophisticated cyber threats." (Read more about what Cato partners are saying about today's news in this blog.) Platform vs. Product: The Difference Matters Cato XDR takes full advantage of the enormous benefits of the Cato SASE Cloud platform, the first platform built from the ground up to enable enterprises to connect, secure, and manage sites, users, and cloud resources anywhere in the world. Unlike disjointed point solutions and security appliances, Cato capabilities are instantly on, always available at scale, and fully converged, giving IT teams a single, shared context worldwide to understand their networks, prevent threats, and resolve problems. As an autonomous platform, Cato SASE Cloud sustains its evolution, resiliency, optimal performance, and security posture, saving enterprises the operational overhead of maintaining enterprise infrastructure. Enterprises simply subscribe to Cato to meet their business needs. Cato's cloud-native model revolutionized security and networking operations when it was introduced in 2016, a fact validated three years later in 2019 when the Cato approach was formally recognized by the industry as SASE. Breach Times Still Too Long; Limitations of Legacy XDR Cato is again revolutionizing cybersecurity with the first SASE platform to expand into threat detection, empowering security teams to become smarter and remediate incidents faster. The flood of security alerts triggered by network sensors, such as firewalls and IPS, complicates threat identification. In 2023, enterprises required 204 days on average to identify breaches.1 XDR tools help security analysts close this gap by ingesting, correlating, and contextualizing threat intelligence information with the data from native and third-party sensors. However, legacy XDR tools suffer from numerous problems relating to data quality. Sensor deployment extends the time-to-value as IT must not only install the sensors but also develop a baseline of specific organizational activity for accurate assessments. Data quality is also compromised when importing and normalizing third-party sensor data, complicating threat identification and incident response. Security analysts waste time sorting through incident stories to identify the ones most critical for immediate remediation. Once determined, incident remediation is often hampered by missing information, requiring analysts to master and switch between disparate tools. No wonder in 2023, average breach containment required more than two months.1 Cato XDR and Cato EPP Expands the Meaning of SASE Cato XDR addresses legacy XDR's limitations. Instantly activated globally, Cato XDR provides enterprises with immediate insights into threats on their networks. Incident detection is accurate due to Cato's many native sensors – NGFW, advanced threat prevention (IPS, NGAM, and DNS Security), SWG, CASB, DLP, ZTNA, RBI, and now EPP/EDR. Powered by Bitdefender's world-leading malware prevention technology, Cato EPP protects endpoints from attack – in the Cato way. Endpoint threat and user data are stored in the same converged Cato data lake as the rest of the customer's network data, simplifying cross-domain event correlation. The result is incredibly high-quality data that improves the incident identification and remediation process. Cato AI uses the data to accurately identify and rank incidents, empowering analysts to focus critical resources on an organization's most important remediation cases. Cato AI is battle-tested and proven across years of threat hunting and remediation handling by Cato MDR service agents. Remediation times reduce as detected incident stories contain the relevant information for in-depth investigation. Cato's tools sit in the same console as the native engines, enabling security analysts to view everything in one place -- the current security policy and the reviewed story. Finally, incident reporting is simplified with generative AI. Purpose-built for investigations, this natural language engine provides human-readable explanations of incident stories. Analysts save time sharing incident information with other teams and reporting to their managers.

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