Altimeter Biggest Challenges Effective MarTech Use Nov2020Lack of skills and budget are two top challenges for digital marketers aiming for effective use of martech, with data quality also presenting a performance gap for some, per Altimeter’s (a Prophet Company) State of Digital Marketing report [download page] for 2020. The report also takes a look at some of the top martech platforms used in organizations.

Whatever marketing teams choose to incorporate into their martech stack, being able to effectively use this technology is paramount. However, the more than 450 digital marketers surveyed indicate that there are a number of challenges currently standing in the way. For close to half (48%), a lack of skills to operate technology is a top-2 challenge, with respondents also being held back by budgets (46% citing within top 2), integration difficulties (37%). Fewer are as concerned with a long time to return (28%) and a lack of customer support and resources (21%), despite suggestions that most marketers want to see ROI from their martech investments quickly.

Taking a look at what, in fact, makes up organizations’ marketing technology stacks, it’s Microsoft Dynamics (26%) and Salesforce Marketing Cloud (25%) that closely compete as the most common primary software used for digital marketing strategy. Used primarily by fewer are IBM (14%), Oracle Customer Experience Cloud (13%) and Adobe Experience Cloud (10%), with platforms like SAP (4%), Marketo (4%) and SAS (1%) not as commonly used as primary software.

In previous research by MarTech Today, monitoring data quality was found to form an important part of the “marketing technologist” role – but a minority of those surveyed by Altimeter feel confident in their data processes. Fewer than 1 in 5 (18%) characterize their organization as deriving continuous and compounding value from data, with a similar share (20%) claiming that data strategy is becoming a core competency in some groups, but is not yet scaled across the organization.

About one-third (32%) are middle-of-the-road, claiming that they have data science leadership and are moving from descriptive to predictive analytics, but about one-quarter (26%) shared that their data is siloed and not in an accessible, useful form. For these respondents, analytics at their organization are largely descriptive and retrospective, but they are actively exploring how to improve their data science capacity.

Fortunately, just 4% of respondents do not have an organizational capacity for data science, nor a plan to develop it within the next 12 months.

Read the full report here.

About the Data: Findings are based on a survey of 476 senior digital marketers across North America, Europe and China from companies with at least 1,000 employees.

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