ASK THE EXPERTS
CAN BIG DATA REALLY BOOST SALES?
‘Big Data’ is a rapidly growing term used by the IT community, but retail IT expert Brian Hume asks whether retailers really understand what it really means or what it could do for their business
B
rian Hume, managing director of retail technology analyst, consulting and training firm Martec
International, carried out an unscientific survey of 15 chief executives a few weeks ago. Only three had heard of the term, ‘Big Data,’ and none knew what it meant. “The most important thing to know about Big Data is that the value comes from the tweets that consumers send and the comments they put on social networking sites like Facebook or blogs,” he said. “This data is unstructured and the lack of structure makes it difficult to process, but there are huge seams of gold in this data. “Typically, an analysis involves downloading
many thousands of tweets and Facebook messages into a database say, for example, of all those that mention the word ‘Tesco’. Then take a manageable sample, say 5,000 to 10,000 messages and manually code them according to the purpose in hand. These coded messages are fed into a rules engine that ‘learns’ from the codes. The rules engine is run against the database to code all the messages and then provide an analysis, based on now structured codes. This process is known as ‘sentiment analysis’.” Hume cited a few working examples: “A
supermarket group found that thousands of people were telling their friends how good a recently launched desert product was. This had not shown in the sales reporting so far because it was new and the reporting lagged the sales. The supermarket concluded that the existing inventory and orders in progress would not satisfy future demand and used the analysis to re-order bigger than planned quantities in anticipation.” Another company analysed what its
employees were saying about it in their private communications. “They found that their employees had a very low opinion of their employer, which suggests very high attrition rates,” said Hume. “The good news is that it gives the HR [human resources] and store operations management time to change HR practices and get employees more highly motivated. A second aspect is that customer service
14 Winter 2014
is probably suffering because of lower motivation. Retailers know that high staff turnover adversely impacts sales due to the number of inexperienced staff on the floor and that sales are higher with happy, motivated employees.” In a third example, a company analysed five of
the top US retailers to see how consumers perceived their on-shelf availability and published a report of the results, which Hume said was very telling. “This type of analysis gives retailers a completely different perspective on availability that you can’t get from internal systems,” he explained. “For example, a convenience store may be out of stock of an important skimmed milk SKU [stock-keeping unit] and a mustard SKU. Both count as one failing in a computerised report on availability and store service level. To the consumer, however, the outage on milk might count as a much bigger failure than the outage on mustard, affecting their perceived view of service level more significantly. These examples illustrate what retailers can do
with Big Data that they could not before without spending large sums on market research. Hume added: “And because this field is so new, the state of the art is developing all the time. ” Hume said companies like IBM, SAP and
MicroStrategy have relevant products or services. “But there is also a growing group of vendors you have never heard of because many of them are start-ups and those are the ones really innovating in many cases,” he added. “You can do so many things with Big Data that
You can do so many things with Big Data that you couldn’t easily do just two years ago
you couldn’t easily do just two years ago, like getting an earlier fix on what consumers think about new products and their prices or consumer feedback on what they think of your own brand products. You can then feed that knowledge into demand forecasting and planning and canvass suggestions for assortment and range additions. “So, can Big Data really boost sales? On its own
it can’t,” Hume concluded, “but using approaches like those I’ve cited, it most definitely can.”
www.retailtechnology.co.uk
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