Analytics: a crystal ball on customer engagement

Since marketing was invented, businesses have been trying to understand customer behavior. The difference in our data-driven era is the availability to quantify that understanding with analytical tools.

“Marketing is now science,” said Dominic Powers, vice chairman of the Asia Digital Marketing Association (ADMA). “Data visualization tools and marketing automation tools are now available for marketers to understand their customers beyond a demographic bracket.”

Tech not an issue
He added that technology is no longer an issue and marketers can easily use these tools to learn more about the customers’ preferences, then build personalized communication campaigns and project their success rates.

Despite the power of data and analysis, few Hong Kong enterprises have embarked on this journey. Powers said that’s due to the lack of a single view of customer data and visibility for marketers.

“The challenge in Hong Kong is its very conservative business culture,” he said. “Look at the supermarkets, there’s no consumer engagement for delivering the right message at the right time–they’re still living in the 1980s.”

But global enterprises with a local presence are slowly bringing the culture of data-driven marketing into the city. According to Powers, Procter & Gamble (P&G) is one of the few organizations able to provide a single view of customer data for marketers.

The journey wasn’t easy, said David Dittmann, associate director, business intelligence of retailer & product supply analytics, P&G.

He attributed P&G’s success to its centralized data governance model. This model, built using Tibco’s analytical platform, allows his team to create different standardized templates to visualize data for different business units and product units across different geographies within P&G.

Journey to data integration
“One of the major changes we made is to develop a data model to enable centralized data governance,” he said. “So the [business] templates look exactly the same for everyone, from the Tide analyst in Guangzhou to the Olay analyst in Cincinnati.”

Dittmann spent two years at P&G’s Asia Business Analysis in Singapore, and said business units “outside the mothership” tend to demand a customized set of data. He understands the challenges of data accuracy within the region, as growing markets tend to bring rapid changes. “But this means the ability to keep a single repository of data is even more critical,” he added.

The centralized platform also enable integration of external information, like data from market research firm Nielsen or social media information, for marketers or business executives to make projections.

Dittmann said one example is the retail measurement tools developed to help their customers: major retail distributors. “It helps retailers to make decisions on the location of a new store,” he said.

Through integrating third-party data, the tool is able to measure the business potential of different neighborhoods in a geographical display. Dittmann said the tool provides data including the number of shoppers within the region, their annual average expenses on certain products, the number of trips they made to physical stores, as well as projected revenue.

Dittmann added that having a centralized data model protects data integrity and also speeds up the creation process for new ideas and practices across P&G’s operations all over the world.

“The discussion is no longer about ‘I have this number and you have that number’ — it’s about ‘we have this set of numbers, what are going to do about it’?” he said. “The centralized data model has changed our operations process, speed-to-decision-making, and corporate culture.”

Lotte.com turns visitors into buyers
Another successful example in the region is Korean online shopping mall Lotte.com. With 900,000 daily visitors and 15 million members, it’s one of the country’s more successful online shopping malls. But that success did not come instantly, said Hyo-Hoon Jung, senior manager, business strategic planning at Lotte.com.

The firm had to deal with different sets of “inconvenient truth,” including a lack of understanding of Web traffic, ineffective marketing campaigns and low visitor-to-buyer conversion rates.

“For online marketers, the biggest concern was the quality and quantity of Web traffic, as well as real-time access to the data,” said Jung. But with investment in Web analytics tools and SAS analytics software, he said Lotte.com built a foundation to transform the company’s online marketing strategy.

The tool allows the firm to measure and analyze different Web traffic data across the spectrum, from basic visitor numbers, page-view status and product-popularity, to heavier analytical insights like identifying potential buyers from their Web surfing patterns, calculating visitor-buyer conversion rates, and measuring marketing campaign effectiveness.

By monitoring visitor’s surfing habits, Lotte.com was able to identify problems in their Web site’s content structure and navigation efficiency. The company then reduced the content on its main page by 20% to allow easier navigation and highlight promotional items.

Jung said the analysis indicated that 60% of the visitors only visit one to two Web pages per visit. To retain visitors on the site and keep them engaged, Lotte.com offers promotion vouchers and coupons.

“We can now see clearly how our visitors move around the Web site,” he said. “We monitor the visitor’s journey from surfing to purchase and build up the database around it.”

The database helps Lotte.com to identify when a regular visitor is seriously researching for a product. With this information available in real-time, a targeted and sophisticated marketing campaign — like sending out product referral promotions — can be delivered to enhance marketing effectiveness and increase the visitor-buyer conversion rate. Jung said Lotte.com achieved KRW2 billion (US$1.9 million) email sales through its product referral database.

Nielsen’s data-driven business transformation
Analytics played a critical role in transforming the business model of global market research firm Nielsen seven years ago.

“We were in an industry that used to produce data and reports 35-45 days after the data period closed,” said Nielsen COO Mitchell Habib. “It was like a report card and didn’t provide actionable insights.”

The delayed information cost the company its major customer — General Mills. “It was a pressure-filled time for us and we needed transformation to data-driven marketing,” said Habib.

Through a partnership with Tibco, Habib said the company developed products that provide retail executives with metrics which integrate real-time transactional data and external market data to monitor their businesses.
“It allows our customers to recreate geographies and categories on-the-fly,” he said. “Things that used to take weeks and months are now done in seconds and minutes.”

Riding on the massive repository of data of five billion global consumers’ viewing and purchase behavior, Nielsen also developed an open data strategy through Nielsen Marketplace: a marketplace where external parties can access Nielsen’s data and APIs to develop and distribute applications.

One of the free B2C applications available through this effort is “Nielsen Top 10,” which identifies the top 10 most popular consumer products in the USA-based on customers’ viewing, Web surfing, and purchasing data.
“We’re in a data-driven business,” said Habib. “[Through the collection of data] we help clients to compete in marketplaces and win customers.”

Eden Estopace from Retail Tech Innovation contributed to this article