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Realtime Marketing: Teradata Combines Big Data and Social Data to Deliver Custom Offers

What happens when big data meets data from realtime social media signals?  Managed correctly, a realtime marketing program creates the opportunity to offer a unique, personalized value proposition to customers.

That’s what Teradata wanted to demonstrate with its “Social Experience” program, which it ran during its recent PARTNERS  2011 Teradata User Group Conference & Expo on October 2-6 in San Diego.  The program, which saw a 20% participation rate from conference attendees, was so successful that it has led to several custom implementations of similar programs for Teradata customers,  and will be repeated next week at Teradata’s Aprimo Marketing Summit.  (Marketing software company Aprimo is owned by Teradata, a big data analytics company.)

Campaign Goals

According to Aprimo VP Product Marketing Deb Woods, Teradata wanted to create an experience that:

  • let customers and partners connect with each other at the conference,
  • introduced them to local vendors and services, and
  • showcase how realtime and customer data could be combined to create tangible marketing value and deliver real returns.
Of course, since the program was built using Teradata technology, it would allow Teradata to showcase its own platforms and expertise.

How the Realtime Campaign Worked

Attendees were invited to opt-in to the Social Experience through a prototype Facebook app, the Aprimo Offer Exchange, to receive targeted offers based on their social preferences. The campaign captured registrant data, matched exclusive offers from San Diego businesses, event sponsors and exhibitors to registrants based on interests and real-time data from social channels–Twitter feeds, Facebook “likes,” and LinkedIn connections.

It delivered the offers according to registrants’ desired methods of communication (Facebook, email, text messages). There were approximately 100 offers from 40 merchants and exhibitors.

Teradata used the realtime data to target the offers based on influence, sentiment and the content that users were sharing.  The company analyzed 3,200 tweets and 6,200 Facebook posts to determine which attendees posted most often, and whose posts were forwarded or retweeted by others. Graph analysis helped visualize the path that retweeted messages followed, indicating the virality of the message and influence of its originator. Sentiment analysis tools helped the team identify positive and negative postings. Analysts also tracked tokenization to understand how users navigated through web sites and which had higher click-through rates.

Based on the analysis across both the structured and unstructed data, the program personalized the attendee experience (program agenda, session schedules, conference e-mails and surveys) and delivered targeted offers and discounts  from exhibitors and local merchants via the Aprimo Offer Exchange for exclusive offers and discounts.

For example, someone tweeting that they were headed to an early-morning session might receive a Starbucks coupon.  Someone posting about analytics-related content might receive a link to a relevant white paper.

Teradata shares more detail on the technologies used to power the program in this blog post, but the campaign ran on a mashup of proprietary Aprimo marketing automation software, a custom-built Facebook app, Teradata data warehouse analysis, and data and business analytics tools.

Campaign Results

  • The Social Experience program in San Diego had 727 registrants (20% participation rate) of a total of 3,500 attendees–a 20% participation rate.
  • The program sent a total of 18,932 personalized offers via SMS, email and the offer exchange Facebook mobile app.  Of those, 6,612 were viewed–which translates into a 35% open rate.
  • Of approximately 100 offers, 89 were acted upon.
  • And Teradata walked away with 12 leads for customers who were interested in buying the prototype application that powered the campaign, with two of those customers likely to implement a custom solution for their own client-base.

Teradata’s marketing team is especially pleased with the participation rate because many of its customers are not very active on social media.  The company has clients in all industries–some, such as retail, are very advanced users of social media, but others, such as its pharmaceutical industry clients, are less active adopters.  In some cases, Deb Woods told me, they found that attendees didn’t even have a Facebook account, so the Teradata onsite staff had to first help people who wanted to participate set up their Facebook.  In other cases, attendees chose not to participate because they restrict their Facebook activity strictly to personal use.

Realtime Marketing:  Best Practices Recommendations from Teradata

The Teradata Social Experience is a great case study in how marketers can combine big data, customer preference and realtime signals to deliver highly targeted offers.  Teradata has a major “Socialization of Data” initiative designed to drive conversation around this topic and encourage its customers to identify and implement programs to drive value at the intersection of structured and unstructured data.

Aprimo CMO Lisa Arthur says that “social networks aren’t simply new channels” but “gateways to volumes of insight. Customers are sending daily – if not hourly – buying signals to companies on laptops, tablets, smart phones and other devices. The Socialization of Data shows companies how to interpret and respond to those signals moving forward.”

But Teradata is far more conservative about how it is stepping into this space when compared to fast-moving realtime marketing start-ups such as LocalResponse, especially when it comes to the issue of the opt-in.

Deb Woods told me that too often, marketers make two mistakes in how they communicate with customers:  1. not getting their permission, and 2. not sending the right offer, at the right time, in the right channel.  By combining realtime data with a traditional data warehouse, an integrated solution such as this program demonstrated can address both of these issues.  ”If you don’t have a pre-existing relationship with me, and if I haven’t agreed to receive communications from you, I will feel like you’re stalking me,” she said.  Companies who don’t follow these guidelines risk brand degradation.

What do you think?  Would you be willing to experiment with a realtime marketing campaign that’s based on a soft opt-in following the guidelines outlined by LocalResponse?  Or would you restrict your campaigns only to programs such as Teradata’s, which require a strict opt-in policy?

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Sam Jones 6 pts

 tonia_ries  Great article, many thanks! You close off by asking for our preference of "opt-in" or "opt out" choice advertising programs.  I'll answer you by choosing, C - "required choice."  I came across this third option in the book, "Nudge" by Thaler and Sunstein. Regarding a different social experiment, "As compared with the usual opt-in approach (you are not enrolled unless you decide to fill out the forms), required choosing should increase participantion rates. One company switched from an opt-in regime to active decisions and found that participation rates increased by about 25 percentage points." p.112 

 

Required or active choice will likely be, if only to save time, an inevitability in future advertising choice architecture.

tonia_ries 117 pts moderator

 Sam Jones I think the key is that the user has to feel that they understand what's going on - and have some kind of choice.  It could even be an "implied" choice - as long as it's clear what the action was that triggered the message from the advertiser.

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  1. [...] @Liberationtech I may not be the best person to ask because, personally, I think the term is as meaningless as web 2.0.  Moreover, big data has been with us since the emergence of the commercial net in 1995 (and of course, before that too), and we’ve always analyzed large datasets both in academia and industry since then.  It’s really more like sensemaking than anything else because once we analyze big data, we extract it from its context, so we can only have very little to say about its structure and semantics.  As a result, for marketing purposes, it’s only as good as polling, except that polling measures people’s attitudes and has longitudinal limitations, whereas big data can enable you to see past and current behavior and track it in real time to see dynamic changes. But as you know, predicting future behavior on the basis of past behavior requires a set of assumptions about a static world that doesn’t exist in practice.  So to make a long story short, if you’re a marketeer, and you want to see shifts in the opinions and sentiments of your consumers in real time, big data is a good tool.   e.g.,  http://therealtimereport.com/2012/02/24/realtime-marketing-teradata-combines-big-data-and-social-dat… [...]

  2. [...] So to make a long story short, if you’re a marketeer, and you want to see shifts in the opinions and sentiments of your consumers in real-time, big data is a good tool.  e.g.,  http://therealtimereport.com/2012/02/24/realtime-marketing-teradata-combines-big-data-and-social-dat…” [...]

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