Adobe Analytics: The Next 10 Years

Ten years ago (2009), Adobe had just launched Photoshop CS4. Customers could get the new offering in a shiny blue box, and it was equipped with an updated adjustment panel and features such as 3D object manipulation. For most people at the time, Adobe was pretty much synonymous with creativity software. So, when the company announced in the Fall that it would be acquiring an analytics platform (Omniture) of all things, many heads turned.

At the time, I was an employee at Omniture, working with brands like Dell to define best practices for analyzing web data and building out AI predictive models. When the acquisition news broke, I wanted to understand how analytics fit into the bigger Adobe story. When our CEO visited a few weeks later, any doubts I had were put to rest. His presentation was a masterclass in bridging our two worlds. He understood that as consumers embraced the Internet and new device formats, bridging data and creativity would become a competitive differentiator for brands.

The last 10 years have seen these trends accelerate at a much quicker pace than most anticipated. Legacy brands that moved too slowly in digital have disappeared. And businesses are now dealing with an explosion of channels, while operating in a world where consumer trust in technology has eroded. The next 10 years for data analytics will focus on helping brands navigate these challenges and become leaders in customer experience management (CXM), through building consumer trust, leveraging AI more extensively and tapping creativity as a growth driver.

Empower brands to build trust

The rise of social networks familiarized a generation of users to the concept of exchanging personal details and interests for free online services. It was not until recently that society fully grasped the extent to which user data was being leveraged and at times, improperly handled. We are at a tipping point now, where consumers are taking a closer look at how they engage with brands and recognize that their data is an asset. Centralized platforms such as social networks will give way to micro-economies, where consumers can transact with trusted brands directly in exchange for more relevant and white-glove experiences.

Brands will have to begin re-evaluating their analytics strategy and data practices as a result. Focus will have to shift towards building deep, direct relationships with customers and a move away from relying on outside data (much of which can be fairly inaccurate in painting a picture of what a brand’s audience looks like). This shift speaks to the future of experiential privacy, where privacy is seen as an opportunity to create stronger relationships with customers through more trusted experiences.

In 2017, Adobe open-sourced the Common Control Framework (CCF) within the Adobe Trust Center, helping brands simplify how they map the compliance strategy with a host of security certifications, standards and regulations (including SOC 2, ISO, PCI, FedRAMP, and others). CCF was originally developed to enable Adobe to streamline its own compliance strategy, resulting in a comprehensive set of simple control requirements—rationalized from different industry information security and privacy standards. It represents Adobe’s continued commitment in providing tools and technologies for brands to pursue a strong security and privacy foundation.

Advance AI for two-way communication with data

Many brands are not utilizing their data to its full potential. With too many channels to count, it is difficult to parse out the most useful insights, and teams are often overwhelmed with ongoing reporting needs. The net result is that brands often falling back on predictable vanity metrics (e.g. insights that make people feel good but drive little action). Brands lack time and resources to go deeper, or waste too much energy chasing the wrong leads. When we introduced virtual analyst in Adobe Analytics, it was our first attempt to tackle this challenge head on and help brands responsibly unlock the power of data. These insights are ones that teams did not know to look for in the first place, but could have a material impact on their business.

The use of AI in this fashion will become a distinguishing factor for analytics platforms moving forward. It will create a two-way dialogue with the data itself, where the AI can begin to learn the most meaningful insights and ways to improve the customer experience. It is a continuation of the harmony that can exist between man and machine, and pinpoints questions that brands should be asking of its data set. AI will continue to fill a resource gap here, being an “always on” assistant that is constantly surfacing anomalies and opportunities that teams can address in real-time. It will also free up data talent for more creative and high-value tasks, helping with laborious processes like data cleansing

Bridge analytics and creativity to drive growth

From the beginning, Adobe saw the potential in bringing more creativity into the enterprise. We knew that our mantra, “Creativity For All”, extended well beyond designers, photographers, and other similar professions. In our view, the principles underlying creativity can be applied to the analytics process as well. While this was an aspirational concept a few years back, it has become nearly mission critical in many cases today. With customer journeys becoming increasingly complex, analysts are challenged with tasks that require more experimentation and new ways of thinking about data.

There is increasing acknowledgement in fact, that marrying creativity and data can positively impact the bottom line. A recent McKinsey study showed that businesses who could combine analytics with human ingenuity, while infusing this into marketing functions, were able to grow twice as fast as those who did not. When we released Customer Journey Analytics in Adobe Analytics, it was meant to be a step forward in helping brands achieve this. We put our first stake in the ground with a creative analytics tools for omnichannel data, made accessible for users of any technical aptitude. Taking cues directly from Adobe Photoshop, layers of data can be curated and stacked on top of each other to form new perspectives on the customer journey. Our hope is that with the right technology, people and processes, brands can begin to better bridge the gap between art and numbers, in a way that can provide rich and meaningful customer experiences.