Embarking on an adventure of discovery with personalised customer journeys


(Published in The Produktkulturmagazin issue 3 2017)

The customer experience ecosystem is no longer a linear paradigm moving from being educated about the products to purchase to support. Customers go online not only to shop, but also to find inspiration to research products and to avail post-purchase services. Enterprises engage with customers along their purchase lifecycle, collect their digital footprints and enrich future interactions. Processing these large amounts of data at optimal levels and delivering on the consumer’s expectations can be challenging even for the most tech-forward enterprises.

The wide variety of digital platforms has come to shape the customer’s perception of what a good and solid online retailing experience should look like from start to finish. Customers use online shops not only to buy goods, but also to find inspiration, research products, and for post-purchase services such as returns and refunds, repairs and marketing campaigns.

Digital plays a crucial role in the value chain and relies on processing large amounts of data and sophisticated technical capabilities to function at optimal levels and deliver on the consumer’s expectations, which can be an overwhelming task even for the most tech-forward enterprises. Most businesses have difficulties in onboarding and accessing quality data due to slow legacy systems and siloed information and have large issues with outdated analytics that won’t connect data and extract helpful insights in real time. On top of this, lacking a master data governance “rulebook” that can structure and make data useful for operations and the decision-making process exacerbates these problems tenfold.

But despite the desire to invest in big data and different data management technologies and good practices, many companies are still stuck in the pilot stage. According to Gartner Research, only 15 percent of the companies have deployed their pre-planned big data project during 2016. Data governance (DG) programs have a way of starting and then fading away. This creates peaks and valleys in an organisation’s ability to know its customers and engage relevantly with them.

It’s not unusual to see organisations on their third or fourth attempt at starting up a DG programme. In fact, Forrester found that 45 percent of organisations govern data inconsistently across business units, and 28 percent focus DG only on data migration or consolidation projects. These approaches tend to treat DG as a systems-up process, with little business-down influence connected to the use of data by business stakeholders or the outcomes achieved through better insight. Achieving DG success and sustainability means shifting toward a performance management approach to data where business priorities and the data principles connect and align.

Master Data Management (MDM) successfully incorporates the principles of good data governance and aligns perfectly with the company’s business priorities and objectives. MDM has well-defined data models, data policies and standards, and pre-established workflows and processes to automate the onboarding and use of master data. MDM accounts for the full lifecycle of data governance spanning all levels from executive to managerial and tactical, across people, processes and technologies and links data directly to the outcome of the customer engagement.

One of Riversands clients is the largest online marketplace in Russia and one of the most trusted brands by local consumers. The company sells worldwide to customers in 56 different countries. Their online catalogue includes a broad range of books, electronics, apparel, health and beauty, food, pet supplies and other household products. A substantial majority of Russian online shoppers view the company as one of their favourite digital retailers. Until recently, the client was solely responsible for building, maintaining and updating product descriptions for all their inventory. Broadly, the company splits their SKU data providers into three categories: Vendors, Vendors Drop-shipping and Business Units. To complicate things further, for all the categories above, they use different product taxonomies for data onboarding and product content enrichment.

The client was looking for a solution that would automate, consolidate and streamline the data onboarding process. They wanted a flexible model that would remove and prevent duplicate copies of repeating data and automatically enrich internal descriptions without manual intervention. The company needed a quick and efficient solution to synchronise and syndicate over two million taxonomies and create a central product catalogue from where they could easily maintain and link multiple products with different relationships. Riversand’s MDMCenter successfully addressed all these challenges and showcased its superior capabilities during the implementation of the first phase of the project. The proposed solution included the MDMCenter for Product Data, Multi-Catalogue and Hierarchy Management with Inheritance, High-speed Data Integration and Syndication, Workflow Orchestration, DQM, UI Localisation, Flexible Data Modelling and Taxonomy Management, a Vendor Portal, and API utilisation by the client’s IT team to enhance features in the future.

Using the new MDMCenter, the client can upload, integrate and syndicate data with ease from a single user interface. MDM enables the management of product hierarchies and the creation of multiple product catalogues. Its advanced ‘fuzzy matching’ technology reformats, matches and links data to display other viable alternatives to the customer and extracts valuable insights from the search and purchase history.

Thanks to MDM, the online retailer can finally use their valuable digital assets to their full potential and drive sustainable growth in the Russian eCommerce market. MDM’s flexibility and scalability have considerably improved the website’s functionality and helped them tackle bigger opportunities. The company expanded their e-travel commerce business and developed smart technologies to connect and support their logistics business and reliably get the right product to the right customer on time and with minimal costs.

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Riversand is an innovative leader in master data management and is leading the next-generation web scale MDM solution offering using big data, NoSQL technologies, functions such as dynamic governance, adaptive workflows, comprehensive user experience and more. Riversand provides a uniform, integrated, scalable, and robust MDM platform that caters to a variety of uses across multiple verticals from small to very large enterprises.

Riversand Technologies Inc.


Picture credit © Buena Vista Images/Getty Images

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