Keeping A Positive Approach to Data Management is Critical to Revenue Traction

Keeping A Positive Approach to Data Management is Critical to Revenue Traction

AI Could Help in Meeting Revenue Goals with Even More Effective Data Management; So do, CRM, Automation and Customer Experience Management Platforms

Today, quality data management and data analytics are at the center of most businesses – and this has happened faster than we could have imagined. Whether you are a fresher or a senior executive, data and the power of analytics that it incubates is rapidly transforming the whole definition of customer engagement and the intersection of experiences. From attracting shoppers to visiting a site, to delivering customer success in post-sales journeys, analytics impacts everyone in the business, especially if you are at a point of commercial transaction.

In their most recent report, CMO Council, in partnership with IBM Watson Customer Engagement, released a deep study on how marketing, commerce, and supply chain leaders fear that there is simply not enough time, budget or patience to unlock all of the data’s potential. The impactful study, entitled “Doing More with Data: Discovering Data-Accelerated Revenue Traction,” lays bare facts related to AI, machine learning, customer experience and revenue churn, based on these new-age technologies.

Here are seven key highlights from the CMO Council and IBM Watson report.

Time, Effort and Money—The Biggest Roadblocks in Unlocking Data’s True Potential

CMO Council finds that nearly twenty-five percent of the respondents agree that they don’t have enough time, patience and/or budget to actually translate all the data they work with into potential revenue churner. While data is the most powerful business currency today, lack of insights could further hamper the way data is mined for making business decisions.

Marketers Could do So Much More to Transform the Way they Deal with Data

Yes! This is the most astounding revelation from the CMO Council report – Marketers find delivering a relevant customer experience is an obligation, a commanding proposition essential to growth, acceleration, and sustainability. Yet, marketers find themselves lagging in the way they deal with the data supply chain – especially with their own internal data assets.

Data Needs to Leave the Marketing Silo and Go Beyond

Marketing teams always had the upper-hand in getting the first look at the data and the resulting analytics. To transform data management, the assets need to move beyond the marketing silo.

The Biggest Obstacles to Extracting Value from Internal Data Assets
The Biggest Obstacles to Extracting Value from Internal Data Assets

The CMO Council report suggests that success with data analytics is possible only when three critical functions – marketing, commerce, and supply chain, work in sync to amplify data strategies.

AI is a Critical Catalyst to Data Enrichment

78 percent of the 165 senior executives surveyed by CMO Council for this report say that they’re exploring into tools enriched and driven by AI in the next 12 months. Committing to the full adoption of AI, nearly one-third of these executives also affirmed that implementing AI would further maximize operational productivity and boost customer engagement.

Marketers Think Sales and Supply Chain Competing as Key Data Collaborators

Top sources of data are CRM, and insights derived from marketing automation, campaigns, social media, financial and transactional data. However, more than forty percent of these marketers also think that sales is a key data collaborator in enabling marketing teams to fulfill overall business goals and priorities. Ranking very close to sales – supply chain are also up there as key data collaborators.

Data Optimism

CMO Council introduced a word- Data Optimism. The word, as analyzed by CMO Council, leads us to acknowledge why it is that working with data is still a ‘hit-and-miss’ projection for supply chain and commerce. And, not for marketing!

According to the report, it’s the business culture and the current attitude in the organizations that hampers data optimism. The attitude is a barrier to making organizations believe that data is actually not that hard to access and use.

Top Technologies to Win Data Game

Apart from AI, of course, the respondents see new tools and toys are critical to data management and data transformation. These tools are CRM, Customer engagement/experience platforms, and user-identity management tools. A dark horse in this race is – Channel/ Partner management platform.

Ranking the Most Important Internal Data Sources by Function
Ranking the Most Important Internal Data Sources by Function

While they may all find themselves originating from different the stacks; they end up serving one greater goal – Doing more business with the customer at the center – sticking to the commitment of delivering what the customer wants.

“The question is not if data is important for any organization with customers… it is if the ability to do more with that data will mean the difference in engagement, profitability, and success,” noted Liz Miller, Senior Vice President of Marketing for the CMO Council.

Liz added, “Each of the functions we surveyed has their own lens that colors and enhances their view into the organization’s data; marketing, supply chain and commerce will all interpret the subtle shadows and light differently, but in the end, they need to be looking at the same picture.”

Other Important Highlights on Data Management 

  • Technologies on the 12-month roadmap and potential roadblocks to implementation and deployment success
  • Key data sources across the organization that are currently part of the customer data value chain and which sources of intelligence are just out of reach yet critical to engagement success
  • Ownership roles and key opportunities for collaboration across key engagement stakeholders
  • Strategies to ensure cross-functional participation in the data value chain, including measures and metrics that define the impact of data application and utilization
  • Success or failures of technologies and platforms already deployed to aggregate, manage and analyze data across the organization

Report Methodology

The research stems from a survey of 165 marketing, commerce and supply chain executives, as well as 12 deep-dive interviews with executives who reveal the ways they are rethinking their engagement strategies through the smarter use of data insights. Those executives hail from brands like AT&T, The Body Shop, Samsonite, REI, Ryder, TD Bank, Cabela’s and Nordstrom.

MTS
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