In my last post, we outlined the reasons why so many retailers fail to take advantage of the e-commerce opportunity and concluded that any solution for driving e-commerce sales growth must provide consumers with superior search capability, personalized promotions, value and convenience. Additionally, the solution must be able to provide all of this in real-time. After all, for a $3 billion online retailer, the stakes are high with just a mere 2% increase in online sales conversions, from 3% to 5%, resulting in sales growth of $2 billion! That’s difficult to ignore.
So if e-commerce presents retailers with an opportunity for windfall profits, then what’s holding them back? Let’s begin by addressing the challenges retailers face in meeting the needs of digital consumers:
1. Product Data Complexity and Management. A typical retailer’s product data is extremely complex – consisting of structured and un-structured data that needs to be ingested and integrated into a database. Disparate and multi-structured data sources include product information, digital images and videos, customer reviews and ratings, dynamic pricing & promotions, availability, consumer loyalty information, and product relationships (e.g. accessories, related products and services). Also in terms of scope a typical electronics retailer may have 70,000 SKU’s in its product catalog while a parts distributor may carry over a million.
2. Issues with Search and Updates. Product-related data changes often with new models, new product innovations, and the addition of new options such as color, size, and packaging. But unfortunately for most e-commerce technologies, e.g., Oracle’s Endeca, the pre-existing schema that determines how the data is to be sorted and searched restricts the number of attributes that can be associated with the data. This prevents consumers from filtering down intelligently through the multiple options available. As a result, consumer search is constrained – and often fruitless! Further, many searches lack context and use a “bag of words” approach without benefit of intelligence. This results in consumers being steered to the wrong product options. Finally, from a development perspective, updating pre-defined schemas is difficult and requires a significant amount of additional coding and time to add in new product features and attributes.
3. Supplier On-Boarding. Part of the problem with Oracle Endeca, and other relational databases, is the need to establish a schema upfront to ingest data. This requirement makes adding new suppliers and product options difficult and time consuming since you’d need to force the supplier to collate and categorize their data into exactly the schema you’ve established. For this reason, distributors often must restrict the number of suppliers in order to cope with the challenges of onboarding slower moving products. This limits sales opportunities.
4. Relationships and context between product data and information. Remember consumers buy solutions to meet their needs, not products. Consider these examples:
In the absence of context or linkages between product data, the retailer loses its ability to cross-sell and up-sell (both in-store and online) via intelligent linked product recommendations.
5. Operational Capabilities. Finally and perhaps most importantly the database needs to provide a real-time view of products, dynamic pricing, promotions, availability, product images and videos. This is important so consumers can close their sales transactions online with the latest product information and in-store sales associates have access to up-to-date information.
A NoSQL database platform provides a flexible answer to the challenges outlined above. Further, by combining an agile, secure operational database with superior search and query capabilities – MarkLogic’s Enterprise NoSQL database offers an ideal advantage as a one-of-a-kind solution for achieving effective e-commerce. Why should retailers sit up and take notice of this technology? Here are some of reasons to give it a closer look:
1. Product Data Management. For retailers the scale and complexity of product data that needs to be ingested is a major barrier that needs to be addressed upfront. MarkLogic is the only database that is optimized to store JSON, XML, RDF, and Geospatial data. MarkLogic can ingest the two most popular forms of document data—JSON and XML—natively, meaning there is no conversion required and no valuable data lost. MarkLogic can also ingest other sorts of data, from RDF relationships to text, geospatial data, binary video files, and PDFs—without the need for conversion. MarkLogic users start with more answers available because they start with better data.
2. Ease of development and changes to product data. One of the major problems with schema based relational databases like Oracles Endeca is that they limit attributes based on which searches can be conducted and are difficult to update. Also changes take considerable development time. MarkLogic is a document style database that does not require a pre-defined schema before data is loaded into the database. Unlike with relational databases, you can change the data without mapping it to a fixed schema or hiding data in opaque objects. You can still store all of the information that you would find in the row of a relational table, but because it is stored and indexed as documents, you don’t have to normalize the data, and you don’t have to worry about how the shape of the data changes over time. This means you save enormous amounts of time and energy that would ordinarily be invested in ETL processes, and you also gain agility later on with future development.
3. Superior search capabilities. MarkLogic provides a superior enterprise search experience with no limitations on attribute search and flexibility to drill down into the data to research alternative products and features. MarkLogic has the search features that user’s expect in an enterprise search application, such as type-ahead suggestions, relevance ranking, facets, snippeting, highlighted search terms, proximity boosting, relevance ranking, and language support. And, just to reiterate, all of this comes built-in with MarkLogic—you don’t have to bolt-on “Search” capabilities from any other solution. This simplifies your architecture, and makes things incredibly easy for DBAs and developers. Having integrated search means one less additional platform to worry about.
4. Semantics to provide context and relationships. MarkLogic uses Semantics to store billions of relationships between associated and linked product types. For example if you’re looking to buy a Samsung HDTV set semantics determine what Cables or Sound Box or Service and Installations are linked with that model. With MarkLogic Semantics you can not only store and query these billions of facts and relationships; but infer new facts. These facts and relationships provide context for better search. MarkLogic leverages those facts in several ways to:
5. Superior operational data warehouse
. Retail e-commerce calls for real-time, operational capabilities. Your data warehouse must be transactional and operational to enable websites, e-commerce and other applications – while at the same time enabling analytics and storage of terabytes and potentially petabytes of data. In business for over 14 years, MarkLogic was the only NoSQL database appointed to Gartner Leaders Quadrant for Operational Database Management Systems. Also, in the 2014 Gartner Report: Critical Capabilities for Data Warehouse Database Management Systems, MarkLogic came out ahead of all other vendors in the customer rating for Operational Data Warehouses.
In summary, e-commerce represents the most significant growth opportunity for Retail. Yet it is also the channel that causes consumers the greatest frustration in terms of search and fulfillment. MarkLogic’s Enterprise NoSQL database represents a transformational opportunity for most retailers – and for sales growth the benefits couldn’t be clearer!
Please be sure to read my other articles in this series:
1. Big Data, Little Insight: Challenges for the Retail and Consumer Industries
2. Removing Roadblocks to Omnichannel 360 in Retail
3. Consumer 360: Reaching Each Consumer With a One-in-a-Billion Message
4. Retailers: Are You Meeting the Needs of Digital Consumers
5. Why do Retailers Miss Out on E-Commerce Opportunities?
6. Reinventing Your Retail Loyalty Program to Win
7. Build Better Retail Loyalty Programs With NoSQL
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