Unleashing experiences — conquering the art of journey optimization

Unleashing experiences — conquering the art of journey optimization marquee

Thriving in the digital era

The roots of ecommerce can be traced back more than 40 years to the 1970s, when early technologies such as electronic data interchange (EDI) and teleshopping laid the foundation for the modern ecommerce store that we are familiar with today. Over time, advancements in digital technology, logistics, and payment systems have made ecommerce more accessible, secure, and convenient for consumers, leading to the explosive growth of online commerce in recent years. As the digital landscape becomes increasingly competitive, companies are placing greater emphasis on delivering exceptional customer experiences. To achieve this, businesses are relying on data-driven decision-making.

Data-driven journey optimization (DDJO) is a process of making decisions based on data analysis with the aim of achieving business goals. It makes sure that the business decisions are based on evidence rather than intuition or gut feelings. It involves collecting the data, analyzing it, finding insights, and then recommending actions to optimize marketing strategies, upgrade services, and enhance the overall customer experience. In this article, we’ll talk about how we can optimize online businesses through this framework by using Adobe Experience Cloud technologies.

The process of achieving key business requirements (KBRs) through data-driven journey optimization presents its own unique challenges. In the early stages, the amount of data available was limited, which made it difficult to generate insights. However, as web analytics have evolved, a wider variety of data types are now being captured, resulting in an enormous volume of data for analysis. As a result, it has become increasingly challenging to derive meaningful insights and present them through a story. Some of the main challenges of doing this include:

  1. Data quality. As the amount of data is high, so are the chances of it being missing or inaccurate. This can lead to wrong insights generation, followed by bad business decisions.
  2. Data complexity. Large unstructured data sets lead to high complexity and can make the optimization process difficult.
  3. Skill and time requirements. The job requires high business understanding and data acumen and takes a lot of time.
  4. Intuition over reality. Bringing intuitions in the insights generation process can result in wrong decisions. The approach should be data over anything else.

A framework-driven approach

Data-driven journey optimization is a methodology that involves using data analysis through Adobe Analytics to make informed decisions aimed at achieving business objectives. By aligning these business objectives with key performance indicators (KPIs), businesses can then map them to different stages of the customer journey to develop a structured framework for analysis. This approach can help generate productive insights that can lead to strategic decision-making. The framework has six different verticals, which we’ll explain in more detail in this article:

  1. Business goals understanding
  2. Mapping KBRs with KPIs
  3. Customer journey understanding
  4. Data-driven analysis and insights
  5. Business recommendations
  6. Value realization

Business goals understanding, Mapping KBRs with KPIs, Customer journey understanding, Data-driven analysis and insights, Business recommendations, Value realization graphic

Business goals and KPIs

The first step toward entering the world of DDJO is understanding the business. What does the company sell? Who is the targeted audience? What are the goals of the company? It’s important for businesses to align their data analysis and decision-making processes with their overall business goals.

Business goals can be diverse, ranging from increasing revenue and market share to improving customer satisfaction and operational efficiency. Whatever the specific goals may be, companies need to identify the key metrics and KPIs that will help them track progress and measure success. Based on business requirements and goals, essential data points for analysis are identified and tracked. Here is an example of one of the areas to understand the framework.

Business goals and KPIs chart

Customer journey

The customer journey refers to the process that a customer goes through when interacting with a brand. It encompasses all the touchpoints a customer has with a business from the initial awareness stage, through to the purchase, and post-purchase experience.

The customer journey typically includes these stages: discover, engage, act, and loyalty.

In the discover stage, users become aware of a company’s offerings through various marketing strategies. Once aware, users move to the engage stage where they evaluate the brand, compare it with competitors, and seek more information. The act stage is when the customer makes a purchase and eventually becomes a customer of the company. Finally, a loyal and satisfied customer may give positive feedback and recommend the brand to others. By using strategies through the DDJO framework, brands can understand and optimize each stage of the customer journey and drive stage-wise conversions for the overall growth of the business.

strategy discover, engage, act, loyalty graphic

Data-driven analysis and insights

The main and most complex part of the whole process is understanding the data and finding insights from it. As discussed earlier, we recommend taking a phased-wise segmented approach while performing analysis. Starting from making the user familiar with the product to converting them into a loyal customer, data-driven analysis would be beneficial.

Keep in mind that you can make many modifications based on the requirements, and you need to perform all these analyses with a segmented approach, like keeping like-minded users in the same group.

segmented discover, engage, act, loyalty graphic

Different analysis methodologies can be used in Adobe Analytics Workspace on each of these analyses, including trends, cohort, predictive, regressive, anomaly, contribution, attribution, funnel, flow, box and plot, and scorecards.

Business recommendations

Business recommendations are specific actions or strategies that are based on data insights and are intended to help a business achieve its objectives. You can gear them toward a variety of areas, such as marketing, product, user experience, customer satisfaction, and more. Some examples of business recommendations may include:

  1. Improve website performance to reduce bounce rates and increase user engagement.
  2. Optimize product development based on data indicating high demand or low sales for specific product features.
  3. Streamline operations based on data indicating inefficiencies or bottlenecks in the production process.

Value realization

The DDJO process doesn’t end just with getting the recommendations implemented. It ends when you analyze the actual performance, confirm whether the actions decided through recommendations have worked, and show the incremental values through Adobe Analytics so similar things can be replicated.

There are a lot of models which can be used to perform value realization. One example is the single-touch or multitouch attribution model. This model calculates the value realization based on the contribution of each website touchpoint to the conversion process. It also assigns a weight to each touchpoint based on its influence on the conversion. There are various methods for calculating the weights, including linear attribution, time-decay attribution, and position-based attribution. Once the weights are assigned, the value realization can be calculated as the sum of the weighted touchpoints that led to the conversion.

You can take past data (for already available experiences), present data (for A/B testing or multi-variants in Adobe Target), or competitor or industrial standards as baselines to calculate the output.

Revolutionize your journey strategies

As the shift in customer demographics from millennials to Gen Z continues, user behavior is evolving at a rapid pace. One such example is the rapid shift toward mobile usage. Around 70% of users of one of the largest banking conglomerates purchased through their mobile phones in 2022, and that percentage is increasing. To stay ahead in this evolving landscape, companies must continuously adapt their strategies. The DDJO framework, applied regularly, has proven to be a game changer. With more than 150% increase in business seen by companies in various sectors, Adobe Professional Services offerings could be the next big thing for your organization.

Contact us today to learn more about Adobe Experience Cloud solutions and stay ahead of the curve.

Aradhana Padhiary head shot

Aradhana Padhiary is a digital strategist professional with more than 15 years of experience in strategy consulting and product management. She is part of digital transformation journey consulting for organizations in the banking, retail, and aviation sectors.

Parth Hetamsaria head shot

Parth Hetamsaria is working in the digital strategy consulting domain at Adobe, where he has made significant contributions over the past one and a half years. With experience in areas such as data, strategy, personalization, customer experience, product, and value realization, Hetamsaria has helped in digital transformations.