Adobe predicts a cloudy analytics future

Helena Schwenk

Wednesday, May 21, 2014 by

During its recent EMEA Digital Marketing Summit in London, Adobe outlined several new features to its Marketing Cloud platform that centre around predictive and advanced analytics. This, we believe, marks a more serious and committed focus from Adobe as it seeks to emphasise the role that data and analytics play in helping engage and connect  with customers and prospects as part of delivering a better digital experience.

Most people associate Adobe with brands such as Photoshop, Adobe Acrobat or good old PDFs, and while this 30 year heritage in digital media has enabled the company to establish itself in the creative marketing department of large organisations, its move into analytics has been a relatively new proposition for the company.

It all kick-started in 2009 when Adobe acquired Omniture for $1.8 billion for its web analytics and targeting technology (now called Adobe Target and Analytics respectively). While this proved to be a great start in the digital marketing space, its analytics’ focus was predominately aligned to descriptive analytics – around the reporting and measurement of online channel performance – and hence was not typically centred on more sophisticated and advanced analytical capabilities. Given the growing tidal wave of digital data that marketing organisations have to grapple with and exploit, it’s perhaps of no surprise to see the company has now sought to augment these foundational capabilities with more prescriptive and predictive analytics.

In fairness, this activity actually started to ramp up last year when the company announced a number of changes to its Adobe Analytics Premium edition, including the addition of anomaly detection (using exponential smoothing), correlation, clustering and predictive customer scoring support. During its EMEA conference the company announced other additions to this list.

As part of a package of analytics enhancements Adobe now has decision tree visualisations within its Analytics offering that provide marketers with  the ability to cluster data and view of predicted paths to conversion from which they can set up rules for targeting, email offers, call centre automation and personalisation, for instance.

Similarly within Media Optimiser (its digital ad marketing offering) the company has introduced predictive modeling algorithms that assess the likely performance of digital advertising campaigns enabling marketing organisations to adapt and optimise ad spend. Then there’s what Adobe calls ‘look-alike’ modeling based on algorithmic models that can identify new prospects whose characteristics and behaviours are similar to your most valuable customers.

Whilst we don’t think these analytic developments will mean organisations are likely to ditch their predictive or advanced analytic workbenches anytime soon, we nonetheless think that Adobe is getting its analytics house in order and becoming more aggressive in how it positions analytics as a core feature of the Marketing Cloud. Its aim here is to underpin each of its offerings with a comprehensive set of analytics services that enable marketers to not only report on current performance but also drive smarter and more forward-looking data-driven decisions. It’s a challenge that its nearest Marketing Cloud competitors such Oracle, Salesforce and IBM also face.

But as we know, analytics is nothing without data. So we’re also pleased to see that Adobe is – at least to some extent – attempting to tackle the challenge of data integration across the various different components of its Marketing Cloud offerings. Live Stream is one such example: this is a real-time event streaming tool that takes data from Adobe Analytics, Target, Social (its social marketing & analytics offering) and Media Optimizer and allows marketers to see what visitors are doing on their sites in real time.

Likewise there is now a unified segment builder within Analytics that enables marketers to build audience segments based on attributes such as gender, region, average order value that can be shared across offerings through a Master Marketing Profile. On first look this appears to be something akin to customer master data management for digital marketing departments. However it’s not entirely clear whether this is just limited to online audience and customer data or would also include offline data sources (such as transactional records or survey information for instance). It will also be interesting to understand how such a capability might interplay with other master data management solutions too.

On a similar note Adobe has also tightened up integration between Analytics and Media Optimiser so they can benefit from each other’s data. Website engagement data from Analytics for instance can now be used within Media  Optimiser, while the results from search campaigns (such as click throughs and impressions) can be used to get a more rounded view and contextual view of campaign performance.

These are all sensible enhancements. Having a more coordinated and joined up data story that crosses its main Marketing Cloud offering should remain an imperative for Adobe, since it brings with it the opportunity to build out more relevant and consistent customer profiles and insights that can drive better digital experiences. Today however the company has a rather fragmented approach to data management and one that is – not surprisingly – heavily skewed towards digital data. Data Workbench, Adobe’s data warehousing tool and its audience data management capabilities are, for example, separate offerings. That said, Adobe is aware of these shortfalls and has plans to build out a more robust set of data management capabilities. What this will eventually look like, however, remains to be seen.

Put together, all of these enhancements represent a bigger push by Adobe behind the Marketing Cloud. This comes at a time when the company has revealed revenue for Marketing Cloud hit a $1 billion milestone in 2013 – a 26 % increase over 2012. If these growth rates carry through to the rest of 2014 then we predict a sunny rather than cloudy analytics future for the company.

Posted in Analytics, Information Management

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