|Friday, 3 May 2019, 16:00 HKT/SGT|
|HKTDC Hong Kong Gifts Fair seminar offers insights into martech strategies|
HONG KONG, May 3, 2019 - (ACN Newswire) - Big data and brand-building are becoming increasingly important for businesses looking to sharpen their competitive edge. By analysing big data, a company can better understand what its customers want to help drive loyalty and develop a consumer recommendation system that can help to boost sales. A seminar on how to use big data to build brands and increase profitability was held as part of the 34th HKTDC Hong Kong Gifts & Premium Fair, presented by Dr Royce Yuen, Co-Founder and Co-CEO of MaLogic Holdings, a marketing technology (martech) company offering innovative business solutions by integrating brand strategies, research insights and big data analytics.
|Dr Royce Yuen, Co-Founder and Co-CEO, MaLogic Holdings Ltd, spoke at a seminar on how to use big data to build brands and increase profitability as part of the 34th HKTDC Hong Kong Gifts & Premium Fair. Dr Yuen told the audience that big data allows companies not just to become bigger, "but, more importantly, to be more profitable by better understanding their existing and potential customers to anticipate what they want and need, and to give them a reason beyond discounts to come back." |
The basic principles of big data
Global research and advisory company Gartner defines big data as "high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making and process automation," said Dr Yuen. Volume refers to the scale of data, velocity refers to the speed of data and how to handle it, and variety refers to all the different forms of data available to companies: in-house data, social media data, and data in the public domain, such as weather-related information.
To these "three Vs", Dr Yuen added a fourth, veracity, referring to the uncertainty of data and the importance of investigating the reasons for anomalies, for example, and a fifth, verdict, which is about understanding why customers buy, don't buy, or don't buy very much.
Making big data work requires four key factors: evaluation; planning, focusing on profitability rather than size; implementation, which means using big data to fulfil customer needs and predict what they want; and monitoring, which requires ongoing engagement and commitment to ensure that big data is used to do things more effectively.
The formula for success
"A brand is likely to succeed if it can serve its customers better than its competitors do," said Dr Yuen. Brands can use big data to offer better products and services, but this requires a cultural transformation to use big data to empower a company. "Ultimately, data allows companies to understand the market and its customers, and why a trend is up or down: whether it is due to service, sales techniques, price or quality, for example," he said.
One theme Dr Yuen returned to several times during his presentation was the importance of not depending solely on incentives such as discounts to develop brand loyalty. "You must provide reasons for people to love your brand," he said. And big data is the key. "Big data allows companies not just to become bigger but, more importantly, to be more profitable by better understanding its existing and potential customers to anticipate what they want and need, and to give them a reason beyond discounts to come back," he explained.
How big data works
Making big data work requires integration, which involves bringing together data from different sources, managing the massive scale of the data, whether in the cloud, on internal servers, or both; and analysing the data, which requires visualising the data to reduce its complexity. The data also needs to be consolidated to identify trends and understand the big picture of where the brand stands in the market and in relation to its competitors.
How big data can make companies more profitable
Big data allows segmentation and prediction, explained Dr Yuen. "Big data allows companies to predict sales by market to manage inventory efficiently and give consumers what they want to build customer loyalty and increase profit." And big data can be used for problem detection. It allows brands to see what their customers are doing and flag problems to anticipate additional problems before they happen. "Retention is critical to sustained success," he emphasised, since it costs much less to retain an existing customer than it does to get a new customer.
Dr Yuen explained that big data can also be used to take advantage of the power of the recommendation system. To illustrate the importance of recommendations in today's marketing world, he gave two examples. "The consumer recommendation system drives offensive marketing much more than advertising does; for example, 35% of Amazon's and 65% of Netflix's sales come from recommendations," he said.
Big data can help maximise profit, said Dr Yuen. Data can help a brand move from transaction mode to relationship mode by aiming at "customer lifetime value". He referred to the 20/80 rule whereby, on average, 20% of customers generate 80% of a brand's revenue, and explained that big data can leverage this by offering different incentives for different customer types to focus particularly on the 20%.
Big data can help build brand connections, he said, returning to his main theme. "It is risky if a customer relationship is built solely on discounts," he maintained, because another company can always offer a lower price. But with big data and the right mindset, a brand can anticipate what people need and present the brand as a solutions provider, building genuine understanding and care about the relationship.
Targeted marketing is enabled by big data, allowing companies to track customer interests and purchases, including what they buy from competitors. It can also provide sentiment analysis to examine the general direction of opinion across a large number of people, using social media.
Operational analytics also benefit from big data, embedding them in business processes so that millions of decisions can be made automatically. Deep machine learning can allow constant refining of this process. Big data can also allow benchmarking reports, with industry sales data, while social listening can provide insights on relative preferences in both "share of market and share of heart".
Finally, big data can help a company ensure that its social involvement, in terms of corporate social responsibility strategies, stays relevant and does not lose touch with how society is advancing, said Dr Yuen.
From the three Cs to the three Es
Big data requires a shift in the marketing mindset, Dr Yuen explained, moving from the three Cs - communication, commitment and conversion - to the three Es of engagement, empowerment and enablement. Engaging customers requires more than advertising, since consumers today trust user recommendations much more than advertising. Empowerment means that consumers must feel the brand's commitment. And enablement focuses on existing customers, making them feel like part of the family.
Digital marketing: content is key
"Digital marketing content is about being a convincing storyteller, through genuine and credible stories that show empathy and understanding, that aren't far-fetched, and that are uplifting, motivational, interesting and rewarding," said Dr Yuen. Today's consumers do not want to be preached to, are not convinced by a shallow message, and want instant gratification, he added.
Dr Yuen concluded by advising companies to start looking at their internal data, social media data, company website analytics and so forth to analyse trends and identify threats and opportunities. They also need to train people to deal with data, and to partner with specialists with a successful track record in their field to ensure their use of data leads to higher profitability, not just larger size. This may require a major cultural shift in the organisation, he warned.
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