Marketing Data Science Opportunities

Aug 2016 • Neeraj Tiwary

• Marketing Opportunities• Customer Life Time Value Forecasting• Customer Segmentation• Customer Churn Prediction• Buyer Personas• Campaign Analysis• Cross channel feedback analysis• Customer Satisfaction Analysis• Real time personalize advertising

• Social Opportunities• Customer Affinity / Profiling• Influencer Marketing• Personalize Messaging / Targeted Marketing• Brand crisis situation analysis• Comparative / Competitive Analysis• Reputation and Brand management• Product Strategy• Social Selling• Content Strategy• Social Media Command Center• Customer Service• Employee Recruitment, Compliance and Activation

It’s not being on social, It’s being social

Social Media as Big Data

What is Social Customer Affinity / Profiling?

• CRM machine learning systems are an excellent way to predict the customer lifetime value (LTV) of existing customers, both new and veteran. LTV is a valuable tool for segmenting customers, and for measuring the future value of a business and predicting growth.

What would be Customer Life Time Value?

How Customer Segmentation enhances reach?

• By discovering patterns in the data generated by many customers who churned in the past, churn prediction machine learning forecasting can accurately predict which current customers are at a high risk of churning.

• This allows marketers to engage in proactive churn prevention, an important way to increase revenues.

How churn prediction is a spot-on opportunity?

• Match the user retrieved through social data with our existing customer database to know if the user is already a customer of Microsoft products or not • If YES, what are the products he purchased so far and his experience of those

products• +, -, or neutral• If it is -ve or neutral, further analyze his comments to know the reason for his negative

comments.• Identify the RCA and provide the same information to product team

• Do a sentiment analysis over all his social comments about Microsoft product which he already purchased. This will give his overall satisfaction level

• Do a sentiment analysis over all his social comments about Microsoft product which he did not purchase. This will give his overall interest level for new / existing products

• If NO, • Do a sentiment analysis over all his social comments about Microsoft product which he did

not purchase. This will give his overall interest level for new / existing products• In case of +ve sentiment, send his information to SALES / telemarketing team to further

contact him.• In case of -ve / neutral sentiment, further analyze his comments to know the reason for

his –ve comments.• Identify the RCA and provide the same information to product team

How satisfied our customer are?

• Uses technology and audience insights to automatically buy and run a display ad campaign in real time, reaching the right user with the right message

Real time personalize advertising

Buyer Personas

• Numerous studies show that word-of-mouth and personal recommendations are seen as far more credible to consumers than newspaper and television advertisements. While such mass advertisements are still necessary because of their powerful reach, these findings show that companies need to increase their focus on more personalized approaches. Clearly, this is incredibly difficult, maybe even impossible, for most companies to deal directly with the countless number of potential consumers. This is where influencers come in……

Who is most influential in the community?

• The number of tweets they make ?• The number of times people mention

them ?• The number of followers they have?• How often they are retweeted ?

What makes someone Influential ?

• Machine learning and pattern recognition can help marketers in a variety of ways. One of the biggest challenges facing marketers is how to personalize messaging to individual prospects and customers so that it most strongly resonates with the recipient. The results of successful, highly-relevant marketing include increased customer loyalty, engagement, and spending.

• Without machine learning, it is simply too difficult to compile and process the huge amounts of data coming from multiple sources (e.g., purchase behavior, website visit flow, mobile app usage and responses to previous campaigns) required to predict what marketing offers and incentives will be most effective for each individual customer. However, when all of this data is made available to computers programmed to perform data mining and machine learning, very accurate next best action predictions can be made.

Personalize Messaging / Targeted Marketing

• This is one of the most popular marketing activities when it comes to social media, and what most marketers struggle with is calculating the ROI on a given campaign.  Usually because we need the dollars spent on the campaign and the dollars generated to perform the ROI calculation. 

• The engagement-level data generated by social media platforms will help us analyze the if, when, and how much activity took place on the individual platforms but to put that in context we’ll need website traffic and financials.  That data typically lives in different systems, so to do effective campaign analysis we need to start bringing that data together.

Campaign Analysis

When customers are talking about us or about our products we want to know where those conversations are happening so we can:

• Interact with interested customers• Get in front of any issues

Who is discussing my product/brand?

• Social media data is very good for identifying problems or opportunities, but more often than not, we’ll need context to act on them. 

• Brand crisis situations are a perfect example. • If the majority of user commentary is of the negative variety,

that's an issue.  The company needs to figure out who this person is and how best to respond to them quickly.

• To do that will involve data not available on the social platforms – Is this person on the boat? 

• The ability to integrate social data with those other systems will make us more effective in these scenarios

Brand Crisis Situation Analysis – Continued…

• Social media has become just another channel your customers interact with your organization. 

• They provide feedback and submit questions just like they’d send an email to a help desk, or pick up the phone to call the call center. 

• From an organizational perspective there is tremendous value in analyzing this holistically rather than the silo’d approach many take today. 

• May respond differently depending on the channel the feedback is coming in.   For example, if we are seeing a spike in negativity about a product on social media, but we aren’t seeing that same spike across our help desks, online forums, or call centers, then maybe we respond with a digital marketing campaign.  However, if the spike in negativity is consistent across all the channels we may have to make a bigger statement

Cross Channel Feedback Analysis

• While the other use cases focused on putting social in context by integrating it with other enterprise data, this use case provides context by leveraging data related to our peers. 

• Rarely in the past have we had access to our competitors’/peers data, but when it comes to social media, we do.  We can access and analyze what people are saying about others products and services just like we can do with our own. 

• For example, if I’m Wendy’s and I see a spike in activity on McDonald’s Facebook page, could I benefit from understanding its cause.  Are they running a new campaign that’s having success? Or are they in a brand crisis situation?  Did someone just find a shoe in a cheeseburger and now there is all this negative buzz online?  If the later, Wendy’s could quickly respond with their own digital campaign, “No Shoes in our Burgers”

How consumers view us vs competitors?

• The means of measuring the ongoing perception of a brand, and remaining instantly alert to any potentially negative developments

Reputation and brand management

• Using the comments of existing and potential consumers to inform future product development

What products got the most buzz and Why?

• Taking advantage of segmentation and other means to identify and sell to potential customers on social media

Social selling

• Listening to audience behavior to optimize content strategy, including SEO research and social media campaigns

Content strategy

• Installation of visually engaging space to conduct campaigns and perform work in the presence of real time data

Social media command center

• Monitoring for customer queries and complaints online, and intelligently responding to them (via partners)

Customer service

• Allowing businesses to manage the processes around staff using social media internally and externally

Employee recruitment

Questions?