Data 101 to Set Your Data-Driven Marketing Ablaze

In this era of modern tech, we are witnessing an organization-scale data downpour. Clearly, there’s a growing focus on data collection and data analytics to drive us away from silos. For CMOs and their teams, data-driven marketing is the mainstay of their marketing and sales operations. With marketing and sales teams looking to unravel data-based insights using data science, there is a need for clarity on how data is managed, used, analyzed and repurposed for better accuracy in campaigns.

In 2017, data scientists grew as one of the most sought-after profiles that companies are hiring. Now, data scientists have become an integral part of organizations. To lead them, there’s a new, pragmatic role of Chief Data Officer or CDO. A CDO is critical to not just marketing success but business success. With new data regulations coming to disrupt the tech industry, the role of CDO can no longer be ignored.

Here’s a quick fact-check on CDOs.

• 90% of large-scale organizations will have a CDO by 2019 (Gartner)

What CDOs Do?

A CDO is a hybrid of technology and business acumen. CDOs are responsible for managing 360-degree data across organizations. Before CDOs become a customary sight, there’re certain elements that need consideration.

CDOs and CMOs can forge a partnership that enriches an organization with insights and makes it data-driven. 

“Marketers will need to start with clean, integrated and organized data on the companies they are targeting, the people within those companies and the relationships among those people. This can be accomplished through a master data strategy that combines a company’s first-party data with third party data and then links this to IP addresses, mobile IDs and data in systems like their CRM to target the right activities by demand unit. The relationships in the buying unit can be determined even before talking to prospects by leveraging analytics to identify potential buying groups. This means marketers will need to be even more of a driver of their company’s data strategy.”

• Rishi Dave, Former CMO, Dun & Bradstreet

Mutual Trust and Transparency Adds Value to Data

The priceless characteristic of data is that its objective. Its number-backed and not based on gut feel. But, data becomes void in terms of business value if decision makers or leaders don’t trust it. Data scientists and marketing teams can be at loggerheads when there’s lack of mutual trust in the data. That hinders the acceptance of CDO’s recommendations, but in the long run is detrimental to business value.

• 87% of marketers rate data as the most underutilized asset (Skyword)
• 56% of companies consider lack of data quality and integrity to be the primary challenge to data-driven marketing (Act-On)

The most effective way ahead to close the CMO-CDO divide is to ensure that data is accurate and consistent. Source tracking, collaborating with data vigilantes, and developing an accessible, transparent echelon of truth is crucial. It hones in a sense of acceptance and makes the same sets of data accessible to the concerned teams. CDOs can convince CMOs to take data-backed decisions when the latter confident about data accuracy. Differentiating data points from the unified source with respect to what’s required is where the run begins. Then, like a relay race, smaller and agile teams can explore those points for validation. This saves the time of both parties in discussing data that is irrelevant.

“By leveraging customer data and piloting specific targeting approaches, companies can zero in on their customers to raise campaign awareness. Whether it’s targeting @usernames to reach customers with similar interests (Follower Targeting), targeting users who follow similar handles (Lookalike Targeting) or Geotargeting, B2B marketers can leverage customer data for a superior reach and better connect with their audience.”

• Bertram Schulte, Chief Digital Officer, SAP

Ambidextrous Input Ranges in Data Streams/Pool

Data scientists and CDOs can amplify business value when there’re no set limits on range and flexibility of data inputs. This will enable them to put the pieces of the data puzzle together and connect the missing dots to eliminate silos. The advantage of doing so is it demacates the KPIs of the data and marketing teams.

Within marketing itself, there’ll be an array of disparate tools for data collection. A CDO’s key objective should be to unify this array and bring it all together on a solitary platform. Data analysis can then be more exhaustive.

• 53% of organizations have initiated an enterprise-wide vision for data analytics (Forbes)

“Not only can marketers benefit from, but they NEED, real-time omnichannel behavioral data to provide the most personalized and relevant experience for customers. The entire point of personalization is to please the customer and build loyalty and lifetime value. And, frankly, a customer won’t be pleased with an experience that doesn’t recognize their latest action with a brand because it occurred with a different device or channel. When marketers can see how a customer behaves across all channels, it leads to a more complete picture of what will be the customer’s next ideal experience. Access to this data and the ability to analyze it across every available channel gives marketers the power to develop a unified marketing strategy that can provide the best customer experience online, in-app, on mobile browsers, through email, through the call center, or in-store.”

• Maribeth Ross, SVP of Marketing, Monetate

Data analytics makes you look savvy but the cake is half-baked if analytics don’t translate into business decisions. Often bias or disagreements are barriers to it. To overcome that, the process of data analytics needs handling by a team of diverse expertise. CDOs, in accordance with CMOs, will have to deploy a team with blended skills. A team of data scientists, engineers, and key marketing ops executives lead to a holistic analytics approach. The results are, therefore, comprehensive in nature. Comprehensive analytics translate into apt business decisions. CMOs need to work closely with CDOs to get the nuances of AI and ML spot on for predictive analytics models.

Making Data More Powerful: Involve Every Stakeholder

The bridge between CDOs and CMOs can close further when they involve business leaders and stakeholders. Discussions around data in a boardroom ought to have a common perspective. CEOs, CFOs, CIOs, CTOs, CDOs, and CMOs, all need to sync in to speak the same data success language. For that, the onus is on the CDO to execute organization-wide data literacy, especially for the senior leadership. Data teams also need to pull up their socks to enable data-driven marketing to accomplish long-term goals.

• 49% of brand executives feel considerable pressure to expand the role of data in their present strategy (Skyword)

The conventional approach of data teams where it was all about offering marketing or business dashboards needs to evolve. Today, CDOs and their teams need to focus on the accountability of the information for mission-critical decisions.

Agile and Focused Teams to Analyze Complex Data

The growing complexity of data calls for adept personnel. It’s time for CMOs to seek decentralized data teams. Centralized teams come good for descriptive analysis. However, prescriptive and predictive analyses require teams that are smaller, cross-functional, agile, and focused. The adoption of such teams has led to another new tag – citizen data scientists. Citizen data scientists are employees outside the data team framework with an understanding of data value. They can handle basic data analytics tools without supervision.

• Over 40% of data science tasks will automate by 2020 (Gartner)
• Number of citizen data scientists will grow 5x faster compared to highly-skilled data scientists by 2020 (Gartner)

Citizen data scientists along with agile, decentralized data teams allow CDOs and CMOs to tackle data complexities.

Lining your Ducks in Order: Why AI and ML is Key to Data Accuracy and Pace of Delivery/Operation

• 67% of marketers consider accuracy to be the most substantial benefit of data-driven marketing while 59% consider speed as the primary benefit (Teradata)
• 63% of marketers have increased their spends on data-driven marketing and advertising over the past one year (MediaMath)
• More than 20% of marketing budgets are for data-driven marketing (DMN)

“We use ML and NLP to help process billions of structured and unstructured documents to curate highly valuable technographic information that our customers use to inform their sales and marketing outreach.”

• Craig Harris, Founder & Chairman, HG Data

“With more and more AI and machine learning capabilities available, we think that the mobile device will continue to grow as one of the most relevant channels in understanding consumers. Real-time location services, mobile app behaviors, calendar settings, language settings, etc. will all help in being able to predict consumers’ behaviors and provide tailored marketing strategies for them.”

• Ari Saposh, VP of Data, oneAudience

The proliferation of AI and ML into data science and analytics will continue. CMOs and CDOs need to have complete clarity on the limitations and possibilities. Game changers in the data-driven marketing economy will be the ones who can align goals and roles of their CMOs and CDOs. Marketing and data teams will have to be in the same boat to resolve complex data issues. That will hatch data-driven marketing as a competitive advantage.