SAS Global Forum 2018 takes place April 8-11 in Denver. The following post is from Sebastian Dziadkowiec and Piotr Czetwertynski, presenters at the event. You can join Sebastian and Piotr for their talk: “An Agile Approach to Building an Omni-Channel Customer Experience” on April 9 at 2 p.m. in Meeting Room 302. We'll also post their presentation here after the event has concluded.
Keys to building a successful and future-proof omni-channel customer experience
Most organizations acknowledge that building a seamless and consistent customer experience is critical to long-term success. The big question is: Now what? With all of the channels to stitch together – from brick and mortar experiences to online clicks – how do you track and make sense of all that customer data? And, more importantly, how do you use that data to create the very best customer experience?
Over many years of implementing SAS Customer Intelligence and helping our clients give their customers exactly what they want and when they want it, our team has identified some characteristics that make for successful projects. Here are some of the key components that most often make or break a Customer Intelligence project.
Time to market
Everyone likes to see value generated quickly and reaching the break-even point for project within weeks of project launch is critical. In case of campaign management, it is possible. Instead of following the traditional waterfall path, with all the IT-heavy components like requirements gathering and analysis, solution design, many streams of implementation and testing, it is worth considering releasing a minimum viable product as soon as possible. Such approach allows us to focus on delivering business value and field-testing all the creative ideas, rather than building an IT system in perfect accordance to requirements, and one that may no longer be relevant at the day of release.
Applying analytics in the decisioning process
Go beyond traditional, rule-based approach to get the most out of the data you have. Nowadays, everyone speaks about machine learning, big data, NBA, artificial intelligence and so on. It is up to each organization and CI project to forge those fancy buzz words into real value, by embedding advanced analytics techniques in the decisioning process. There are many ways to boost various use cases by the advanced methods; make sure you will be able to use all you need and integrate their results seamlessly, regardless of when and how you engage with your customers.
While working on a CI project you should also keep in mind other areas: project organization, building a future-proof solution that will stay relevant for years, and constant search for additional opportunities to use available data and solutions to generate incremental value beyond the core scope of customer intelligence project.
There isn’t a one-size fits all approach to implementing a CI project, but these lessons learned can greatly increase your chances for project success – successful delivery generating a high ROI in a short timeframe while staying relevant in the long run - through the very best possible customer experience.
Find out more at the SAS Global User Forum 2018
Join Sebastian and Piotr for their “An Agile Approach to Building an Omni-Channel Customer Experience” Breakout Session at SAS Global Forum April 9 at 2 p.m. in Meeting Room 302.
About the Authors
Piotr is Customer Analytics Manager in Accenture. He has 11 years of experience in Campaign Management and Analytics. Currently he is one of the people responsible for launching of Accenture Center of Excellence for SAS CI in Warsaw, Poland.
Piotr recently focuses on solutioning & strategy in the areas of campaign management, BI & Analytics.
Sebastian has 8 years of experience in technology and management consulting, mostly in communications industry. He went through the entire project lifecycle on numerous engagements, starting from programmer, through business and technical analyst, up to solution architect and team manager on large-scale analytics projects.
Sebastian specializes in analytics solutions technology architecture, particularly focusing on customer intelligence and big data. He serves as technology lead in Accenture Center of Excellence for SAS CI in Warsaw, Poland.