Adobe Analytics: making data easy

Mention data or data analysts to the uninitiated and you are likely to be met with glazy eyes, or jokes about how ‘all that stuff goes right over my head!' But to a digital retailer, data analysts are the superheroes and data the superpowers without which many businesses simply couldn’t survive.

Today, it’s not just the sheer amount of data that sends most departments running for cover: it’s learning how to understand it, organise it, share it around the business and make the best use of it quickly and effectively, that causes so many difficulties.
 

Step forward Adobe Analytics, an innovative analytics solution that solves many of these issues.
 

Working like a dozen superheroes combined, Adobe Analytics delivers the ability for anyone in the business to understand and optimise how their customers interact with their brand, taking in all touchpoints in real time and at scale.
 

SQLI spoke to Adobe Solutions Consultant, Ashika Ramjee about the quickly evolving data sphere, and how Adobe Analytics can help businesses harness its power easier than ever before.

Why is data so important to digital brands today?

It’s almost impossible to win over today’s tech-savvy consumers using marketing alone. Today’s marketing strategies are completely data driven. Brands have to know what their customers need, what they like and what they’re willing to buy. This is all expressed in the data.

The modern consumer journey is a lot more involved and Covid has had an impact on buying habits. Customers may read your blog, click on your website, but still not buy a product until an ad pops up on their search engine. These types of journeys are essentially a footprint of data. Businesses can capture this data to really understand their customers and understand how they relate to their digital brand. This also allows them to optimise and personalise customer experiences better.

Data also provides businesses with greater insights and best decision making, driving their marketing strategies, setting strategic goals and making smart investments to further grow the digital brand. Essentially, collecting the right data provides more informed decisions overall.

Have you noticed any new trends in the data sphere?

There are two trends emerging right now. Firstly, there is a deprecation of third-party cookies with some browsers no longer accepting third-party marketing cookies – as well as the introduction of the likes of ITP 2.0 which is a challenge for digital brands by limiting cookies further. It means brands are having to take certain measures and mitigate against the effects of data tracking, with more focus on first party data.

It will be vital for brands to have a solution that not only adheres to these measures but gives them the ability to gather a rich data set to support a holistic view of customers as well. The flexibility to derive relevant data from different systems and channels will be even more important.

Secondly, there is a higher demand for self-service analytics, meaning a need for democratised data across different teams in and outside of marketing that can be easily shared. This will not only foster collaboration between key stakeholders, but allow them to make informed decisions and comfortably analyse the data on their own.

With this in mind, an intuitive analytics dashboard is imperative, while the emergence of automated data insight with AI machine learning is now of peak interest.

What are the main challenges for brands regarding data, today? 

I see three main areas. Firstly, as previously mentioned, the issues regarding state regulations and the privacy and consent around these which diminishes the level of data that can be collected. Secondly, brands still have a limited view of their customers’ omnichannel experiences which can lead to out-of-context reporting and how to build experiences that way. Thirdly, many businesses’ digital data still sits in silos, meaning it is collected and stored in different places which dilutes the quality of data sets.

All of these make it very difficult for brands to truly understand the customer journey to make business decisions and build brand loyalty.

As well as the collection of the data, understanding this data can be challenging. There’s a need for more approachable and intuitive analytics solutions. Not only do user-friendly dashboards make it easier to identify what campaigns are underperforming, but it’s now important to automate gathering these insights to set, define and achieve goals sooner.

The progression of AI machine learning capabilities will enable brands to better understand their customers and meet these expectations much quicker.

Why do digital brands need an analytics solution?

An analytics solution brings data to life, unifying it all and helping inform decision making, predict outcomes and prescribe actions.

Brands can find out the answers to questions they may not have even thought of. They can determine how customers are navigating across the site and find out what is driving conversions, identifying groups who are showing brand loyalty. They can then tailor experiences for each of these individual customers to drive acquisition and for customer requisition too.

The right analytic solution can support these insights across the whole customer journey. It can help them have in-context insights to act with marketing campaigns, helping drive strategies quickly and intelligently to grow the brand. Analytics really powers businesses in this respect.

How can Adobe Analytics help?

Adobe Analytics delivers the ability for anyone in the enterprise to understand and optimise how their customers interact with their brand, across all touchpoints, in real time and at scale.

Firstly, it provides a unified platform to collect, store and process digital data – allowing brands to measure the effectiveness of their digital experiences which is critical for optimising marketing efforts such as personalising experiences, driving better ad spend and monetising content and campaigns.

Secondly, brands can better understand the complex multichannel customer journey we see today where they are interacting with multiple devices and going across different channels. Having this in Adobe Analytics means they can see and remove any pain points from the customer conversion process and therefore deliver positive experiences in the moments that matter.

Adobe Analytics can also translate data into insightful information for brands to act upon; there’s an easy drag-and-drop for audience building and customising reports, for instance, that brands can improve business performance through.

What would you say stands Adobe apart from other analytics solutions? 

It’s future-proof and acts as a custodian to hold your data, meaning businesses still own it. With a lot of other solutions, data ownership may reside with them instead. This creates a large conflict of interest and distrust with brands.

Adobe Analytics also captures your actual data, with no concept of sampling. Other solutions use sampling as part of the overall data, running the risk of introducing inaccuracies and stunting the growth of the brand.

Another one would be flexibility. It’s a single platform that can manage the needs of a business from omnichannel insights in real time, to individual customer analytics. All of this sits in one solution and integrates with the wider Adobe platform and offers data flows between the systems.

What are its most important features?

It has an approachable dashboard interface – which allows you to share insights among the team easily. It’s a huge canvas for building workspace projects, so you can drag-and-drop data, instantly create breakdowns to look at customer journeys through visualisations and create segments. It’s very intuitive.

It also has AI machine learning at its core. Our framework, known as Adobe Sensei is a clear differentiator when integrated. Adobe Sensei is an artificial intelligence (AI) tool that integrates with the Adobe Experience Cloud. It brings the power of AI and machine learning to experiences – deepening insights, enhancing creative processes and accelerating tasks and workflows.

In my opinion, organisations need this to stay relevant and remain competitive in the future. Analytics has a feature called Anomaly Detection that automatically goes through thousands of combinations of your data and data points, identifying statistically significant anomalies you may not have thought about. It also answers why these have occurred. With Sensei, this feature can increase insights and plan to action. For example, it can automatically detect a spike in revenue attributed to a certain campaign and geography. You can then understand what your customers want and how to provide it for them more effectively. When these anomalies occur, you can even be alerted by an SMS or email.

Another feature is Segment IQ, powered by Adobe Sensei again, that can be used to look across different behaviours and traits of target audiences. This provides brands with details of what these audiences are looking for, helping brands get to know their audience better.

What are some favourite features according to merchants or digital agencies? 

Adobe Sensei is a hot topic – and how it’s applied to customer journeys is more of an increasing interest. With so much data, brands are increasingly interested to see how they can automate their processes.

What’s one thing not really understood about Adobe Analytics?

Some brands don’t realise it integrates with the wider Adobe portfolio with it all sitting on Adobe Experience Cloud.

If you integrate Adobe Target for example – to utilise target audiences and personalise experiences – when deployed on Adobe Commerce, the results seamlessly flow back into Adobe Analytics so you can dive deeper into why an experience outperforms another experience.

This cohesive nature allows brands to optimise customisation and marketing investments much more efficiently and effectively.

Can you give some examples of how Adobe Analytics has helped businesses?

One major brand in the aviation industry integrated it to help them bring data across multiple channels, such as web, mobile, email and so on, to create a 360-degree view of how their customers responded to digital campaigns and experiences. This insight allowed them to design more personalised deals and relevant experiences, which led to a 60 per cent rise in average spend per customer.

Another customer was interested to know if the new calculator that they had built for calculating loans on their site, was having an impact on conversions. They used Segment IQ to compare several segments to see how this calculator improved business, in which they found that the calculator improved conversions by 4 per cent. This led to them placing the calculator in the top area of their website which led to not just a 4 per cent conversion, but over a 10 per cent conversion lift on their loan application process.

Finally, where do you see data and analytics heading in the future?

Historically companies have been focused on the “easy button” which are 3rd party cookies. Buy several ads and fill the top of the funnel. It’s a scale game. The more you pump into the top of the funnel the more conversions you get at the bottom. Once that scale goes away, every visitor to your brand counts and you need to analyse and understand the behaviour to really serve the needs of the customer and provide a better experience. Build brand loyalty and see the fruits of your labour.

Based on this we’ll see a future where businesses focus more on individual-centric personalisation, rather than it being about the masses. Having a customer data platform where you can stitch behavioural and known data, and using AI/ML to provide further intelligence for your analytics solution is key. This allows you to gain a better understanding of each individual customer to help drive more personalised experiences and marketing initiatives.

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