Bart Molenda, Head of Paid Acquisition at Square, explained how marketers can use data science to take a data-driven approach in their day-to-day efforts in his keynote presentation to Argyle’s CFO membership at the 2017 Financial Services Forum: Marketing & Technology Innovation in San Francisco on September 14. In his presentation, “Leaning on Data Science to Drive Marketing Performance,” Molenda described how data science plays a key role in helping marketers obtain better insights, extract actionable information and grow a brand.
According to Molenda, marketing has transitioned from an art-based department to a data-driven one. As such, today’s marketers are responsible for data tracking and analysis, and marketers who fail to embrace these tasks may struggle to engage with prospects and customers.
“We’re doing a lot more decision-making based on massive amounts of data that are coming in to our businesses,” Molenda said. “It’s not as much about the art (in marketing) as it is the science.”
Marketers are monitored closely, due in large part to the sheer volume of data that is available. Fortunately, data can be used to help marketers assess the value that they are providing to a business and its clients.
“We’ve become accountable for the value that we return,” Molenda stated. “I think that’s what we’re ultimately measured on.”
Data science is reshaping the way that marketers examine data, and for good reason. With data science, marketers are better equipped than ever before to speed up and enhance their data analysis. Plus, data science empowers marketers with the ability to analyze data from myriad online sources – something that could help marketers discover innovative ways to foster long-lasting customer partnerships.
“Data science can be used to create logical groupings of what’s most important and the things that follow under that.”
At the same time, marketers sometimes try to track and analyze too much data at once. This may lead to data overload, which forces marketers to miss out on actionable business insights.
“As data sources have become more widely available, data science can join them,” Molenda noted. “Although you can create models that are super interesting, these models can become exceedingly complex.”
Ultimately, marketers should use data science to understand a company’s strengths and weaknesses, Molenda said. With this approach, marketers can find out how a company can transform assorted weaknesses into strengths.
“Data science can give you a view of whether what you’re doing now is working, but it can’t tell you what else you should do,” Molenda said. “I think imagination and creativity are important ingredients that you have to bring into data science to get exposure to the different realms that you can work on.”
Furthermore, data science can lead to meaningful website improvements.
“Data science can give you a view of whether what you’re doing now is working, but it can’t tell you what else you should do.”
If marketers track and assess website data over an extended period of time, they can uncover various patterns and trends that are hidden within the data itself. Then, marketers can use these insights to deploy actionable website improvements that may lead to increased customer retention and business revenues.
“Data science can be used to create logical groupings of what’s most important and the things that follow under that,” Molenda indicated. “Matching the right page to the right keyword to the right copy is a big task, and data science can play a big role in [simplifying] that task.”
Molenda also outlined seven potential marketing projects to implement using data science:
- Keyword Hacking Using Natural Language Processing (NLP) for Search and Topic Modeling: Marketers can find out which keywords, topics and content are generating interest from consumers and tailor a business website accordingly.
- Google Trends Data Mining for Competitor Campaigns: Marketers can learn about the competitive landscape across any industry, at any time.
- Email and Lead Prioritization: Marketers can use data science to discover which leads are most likely to become sales conversions.
- Customer Targeting: Marketers can move away from customer personas and target customers directly.
- Predictive Customer Outreach: Marketers can determine the best times to reach out to customers, as well as how many times that they should try to contact a customer.
- Clustering to Understand Potential Customers: Inferred data can create associations that show relationships and new opportunities in customer groups not yet identified.
- Optimal Spend Analysis: Marketers can better understand their spending than ever before to avoid wasting precious time and resources.
Data science provides a valuable opportunity for marketers around the globe. It enables marketers to get the most out the data at their disposal and generate actionable insights day after day.
If marketers deploy data science, they could help a company gain a competitive advantage over its rivals. Perhaps most important, data science can lead to business improvements that enable a company to accomplish its immediate and long-term goals.
Bart Molenda oversees Paid Marketing Channels for Square. He leads Customer Acquisition and has over 15 years experience in Marketing. Prior to Square, Bart worked in marketplaces overseeing marketing strategy for several large global classifieds brands owned by eBay.