Understanding the customer journey

Those who think that the digital transformation and the changes it brings have already reached their peak are mistaken. It is only at the beginning and should bring a series of changes – both in business processes and in purchasing habits – that are still unknown. Some of them, which were considered unimaginable a few years ago, are starting to strengthen and show that they should consolidate in a short time.

One of these transformations concerns the consumer experience. We are already used to the concept of the buyer’s journey and the importance of using data correctly and efficiently to ensure the best shopping experience. If you still don’t care about your customer’s shopping experience, it’s a good place to start, because the market is taking the first steps towards expanding this experience, now thinking about the customer’s life experience.

The concept of a lifetime journey takes into account not only the purchase journey of a purchase, but also all the journeys it may be involved in at the time of purchase.

This life journey concept originated in the pharmaceutical sector, but it’s only a matter of time before it starts to be used in other areas, such as retail. This is because it takes into account not only the buyer’s journey of purchase, but also any other journeys he may be involved in at the time of purchase. It’s about understanding how the journeys of food, wellness, exercise, education and more can be combined through one vision, turning them all into the journey of a lifetime.

In the field of life sciences, the concept of life’s journey has been put into practice mainly in the correlation of disease and treatment. For example, patients connect with financiers, insurers, healthcare providers, pharmacists and other healthcare professionals throughout their journey, but these interactions are often independent and rarely connected. That is, the doctor may know that the patient already has a condition or other disease, but he or she has no way to share that information with the pharmacist.

With the new approach, the patient journey should not only be about treating symptoms, but connecting with people on a human level. Healthcare providers must achieve this by finding ways to connect with other journeys within a person’s orbit.

Importance of data

The same applies to other areas, such as retail: companies should look for other journeys that involve their customers. Some conducted experiments. An example is the automotive industry, whose latest releases have sought to highlight how important a car can be in the various journeys of its customers, rather than simply highlighting the product’s qualities.

It is about the fact that, both in the pharmaceutical sector and in others, the construction of this life path fundamentally depends on data. Bringing the concept into real applications involves gathering information across the shopping ecosystem, across social networks; passes using machine learning; and, above all, it involves the effective use of technology, with machine language learning and natural insight development. Fortunately, technology can play a significant role in shaping that future, filling in the gaps, enabling deep collaboration, and making life’s journey an achievable reality.

All this, of course, will depend on the path of digital transformation of retail. At this moment, it is important to bet on CDP (Customer Data Platform) which can act as a powerful agent of change not only in processes, but also in the way you look at the customer. Here are five tips to make this happen:

1. Relearn customer needs, tastes and behavior

Creating a unique 360-degree view of the customer that is also actionable is the most important step in creating superior CX for customers. A CDP needs to be able to take in a lot of data from multiple sources – e-commerce, mobile apps, stores, kiosks, CRM, ERP, DMP, etc. – and combine, remove duplicates and fill in the gaps with any customer data that might be missing. While most of this is explicit data captured in other systems, advanced CDPs can also gain implicit insights into search intent, past purchase affinities (such as brand and/or category affinity), and more. CDP can also analyze this aggregated customer data using advanced AI algorithms to create granular and similar micro-segments of “best customers” or families, and track and analyze customer segments and their migration as they emerge, enabling retail marketing to drive personalized engagement across the board. customer life cycle.

2. Real-time user engagement

In marketing, everything is about timing, and this forces brands to communicate more often, especially in the key “moments” of the trip. CDPs can provide real-time audience activation, which helps orchestrate relevant campaigns and communications before they leave their properties. Engaging with customers in the moment is a key differentiator that few retailers can boast, and real-time CDP makes it possible.

3. Scale adjustment

With the deep knowledge of customers and personas provided by CDP, retailers can enable a personalized 1:1 customer experience. Modern CDPs add an advanced personalization module, which should be context-sensitive, and a continuous algorithmic testing engine, which ensures that the right decisions are made automatically with every interaction in real time. From landing pages to the entire store flow, retailers can provide a highly relevant and engaging experience, improving customer satisfaction and conversion. The latest innovations include deep learning-based recommendations, where retailers can digitally replicate a rich in-store experience with advanced visual artificial intelligence and NLP/text personalization in real-time, mimicking human management.

4. Data security and privacy compliance

Building trust between brand and customer is a business priority. As GDPR and other regulatory requirements become mandatory, CDP helps manage known and unknown personally identifiable information and agrees to comply with these regulations. Laws and regulations surrounding data protection have made consent-based first-party data collection more important than ever for businesses.

5. Match demand with supply

Perhaps most important and challenging is connecting the CDP to the core of your retail business. One pitfall to avoid is treating this investment as another silo. A retail-centric CDP collects demand-centric data and combines it with customer-centric merchandising and customer planning. With machine learning-based algorithms for demand forecasting, assortment planning, store grouping, pack size optimization, product rationalization and discount pricing, retailers can ensure the right availability at every point of sale, including the store. and digital in line with the customer journey and better personalization.

Trust is key

Another key point for building a life path is gaining the trust of customers. This is often something that many brands take for granted when it’s earned, but everyone understands when it’s broken. While it is imperative to make the most of the data you have to optimize the user experience, all of this must be done with data privacy in mind.

Doing this effectively while building trust will require more than just understanding privacy rules and regulations – it will require transparency, user-informed content, and privacy design at every layer. And that will require looking into the future – what consequences might arise if you share that data with third parties, even those you trust?

At the end of the day, customer experience and satisfaction are key measures of your brand’s success. So it’s critical to get the most out of your data and understand what’s happening in every user interaction. By taking a holistic and comprehensive view, harnessing the power of data to inform your AI-powered solutions, and doing it all with consumer trust as a priority, you can optimize the customer experience.

I recently experienced a practical example. I was out of my state, I was traveling, when I needed to change the battery in my car. I bought it from the manufacturer’s online store at 11:30 pm and the next day at 7 am the repairman was there. I was worried about losing the car’s settings (trip computer, etc.), and the app asked me this after some time studying the purchase alternatives. Behind it is predictive intelligence and a database that has had correlated errors in the past. That way, the assistant arrived ready to attend to me and aware of my concern.

The fact is that at the end of the day there is pain that needs to be treated and if possible, quickly. If the entire orchestration behind that service has a break or gap, it will be lost. We hear a lot about data lakes, but if there is no assertiveness and speed, this pause occurs. Not only is the solution important, but so is its adoption, along with full culture and user engagement, to ultimately impact applicability in the user journey.

Going back to my car incident example, from the digital platform experience to the maintenance technician, everyone was engaged and in tune with not just the “pain” but the concerns. Behind this is a strong CDP and an engaged team, which are now very important steps towards building a life path for a company that wants to fully engage its customers.

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