How to Develop Tools for Great Customer Experience
It's not all about the raw code. The companies that will pull ahead in 2018 are those who integrate a client-first approach throughout their development teams.
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Buzzwords like “omnichannel,” “seamless interaction,” and “digital touchpoints” were offspring of the push to mobile everything. Business leaders are expecting their dev teams to deliver on all of these promises and more. Easier said than done. Here’s how successful teams are translating “great digital experience” into real solutions.
Getting Into The Mindset
Software developers are working across industries, especially in retail, to develop online and digital tools as quickly as possible with minimal manual input and maximum customer satisfaction. In addition to the technical tools required, all developers (and really, all employees), need to adopt an experimentation mindset. Every business and customer subset has different needs, making a single “fix” an impossibility. Developers and employees should be open to iterating and letting the data answer the question as to whether something was successful or not, instead of just the highest paid or most senior person. Successful retailers often run dozens if not hundreds of experiments every year (really large ones often run in the thousands) on a range of ideas from page layout to new algorithms like using more advanced search ranking algorithms.
It’s All About The Follow Through
This iterative mentality is an important foundation for testing and developing new tools, but it’s not everything. Developing new tools should always be followed up with accurate performance measurement. These tools should support measuring whether an experiment was effective or not and then turn it into a full production system as quickly as possible. Additionally, tools to support this trial-and-error mentality shouldn’t come at higher costs. Tools should support driving down the cost of experimentation so that running more experiments to create optimal customer experience isn’t cost prohibitive.
The simplest way to do this is to think about the lifecycle data goes through as it goes from raw capture, through marketing and data science, and then into IT/Ops, and look for places to short-circuit those processes while still being able to quickly develop and deploy. For instance, in many companies, raw user data is captured in an analytics tool like Adobe and dumped out to a data lake where the data science team builds models before handing off a prototype to engineering, who then must turn it into production-ready code. If all (or most of the team) can run on a shared analytics platform that is able to quickly and easily publish to production, significant time can be saved, which enables more experiments to be run.
Breaking Down Communication Silos
Businesses that have been successful with creating great customer experience know that communication between departments is critical. The biggest challenge digitally driven organizations face is breaking down the silos of who owns customer data and making sure that it’s shared appropriately. From marketers, to developers, to data scientists, different departments have their own vantage point of the customer experience. In order to build the best tools, dev teams need to see the customer from all sides. Once developers have access to the data and understand its implications across the organization, they can incorporate production-ready machine learning and NLP models, real time data like inventory, margins, user behavior, seasonality effects and pricing into ranking and recommendation systems to improve a customer’s digital experience.
Meeting Customers Everywhere They Are
Improving the digital experience is no longer just a priority for online platforms. In an effort to create better in-store experiences, and make the transition from online to in-store more seamless, companies are increasingly relying on digital tools to help customers browse and buy in brick and mortar locations. This next wave of digital customer experience comes with its own set of challenges for developers.
Companies want to deliver results that are optimized towards the user being able to immediately go find the item and purchase it, perhaps even guiding them to the actual aisle the product is in. This means incorporating store level details into the search (ideally without having to maintain a separate stack from the online version). Also, the customer isn’t as transparent in-store as they are online. If the user is using a kiosk in the store, it means developers don’t have many of the signals about who the user is or what they bought like they do in an online experience, so it is harder to personalize results.
Getting More Done With Less Work
Assuming the AI-train continues, dev teams in 2018 will be under ever-increasing pressure to deliver more production-ready machine learning and NLP features that personalize a user’s experience with a minimal amount of manual work. The companies that will pull ahead in 2018 will need to constantly experiment, work more collaboratively, and find innovative ways to meet the customer in order to keep bringing these marketing buzzwords to life.
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