Tag Archives: Customer Analytics

Do companies REALLY care what customers think?

If not, they should! And there is a means to truly understand customers…

Social media analytics seems to be all the rage and for some, it is the Holy Grail to understanding customers’ needs, wants, desires, and opinions.  While much has been done in the realm of customer analytics, this has largely been focused on historical analysis of data behind the firewall.  This only tells one piece of the story.

Social media analytics enables organizations to add that missing link in customer analytics – sentiment.  What do people really think or feel about a product or service.  Yes, you can infer this information from historical purchase history or marketing/sales interaction history – But isn’t is just downright more accurate when you read something like: “This is the most USELESS product ever!”  or “I cannot believe that anyone would pay money for this piece of crap!!!” or “Hey, airline X!  A $10 voucher is not going to cut it this time!!!”

For you marketers out there, social media analytics can be a powerful ally as you determine how to position your offering, to whom and whether or not your messaging is resonating.  Social media analytics enables you to determine:

  • Who is speaking about your product – where are they from and what is their demographic?
  • Is the overall sentiment negative or positive?
  • What other topics are people speaking about which are related to your offering?
  • Are the people key influencers?

Now, many organizations, including marketing, make the mistake of looking at social media analytics as a stand alone set of information.  Those who see social media as a complementary data source will get a better picture of their customers and prospects.  Bringing Social Media analytics into the mix is part of a solid customer analytics strategy.

Tactically speaking,  marketers need to act on the information gleaned from social media.  Navel gazing will get you nowhere fast…….

Here are a few examples of companies responding to a social media crisis:

Big Data – big deal or big hype?

Big Data is a reality.  Big data is also big hype. So where is the real value in the Big Data hype?

Like it or not, Big Data is a reality marketing and other organizations are facing today and will face well into the future. According to the IBM Global Technology outlook, it is estimated that data growth will explode exponentially from 3,000 exabytes today to 9,000 exabytes by 2015. (I had to look up the word exabyte!) So what do we marketers do about incorporating this new source of data?  Where are the best use cases?

We are faced with a challenge – Big Data alone does not help us.  We need ways to get value out of the data.  The challenge is that traditional analytic tools are not exactly suited to take advantage of Big Data.  Analytics vendors are developing offerings in an attempt to keep up with the ever changing needs.  With that said, we need to be thinking about where it fits in.

For me, the best use case is squarely in the camp of customer analytics.  I love my data from the marketing automation system.  It tells me a great deal about the patterns and behaviors my customers and prospects display.  But it only gives me a piece of the puzzle.

As I think about my customer marketing initiatives, I need to be able to prevent customer defection (commonly known as “churn”). By leveraging unstructured data (call center notes, customer interactions, survey responses…) with internal structured data to detect & proactively mitigate factors that lead to defection,  I can better design marketing programs to avoid that “aha moment” when customers realize they no longer want to do business with satisfaction surveyus versus defecting to a competitor.  Conversely, applying the same approach can help marketers identify the “aha moment” which leads to improved customer loyalty

So, is Big Data hype or is it really something we marketers can benefit from?  If marketing organizations do several things, I believe it will improve marketing’s ability reach the target audience with more appropriate offers.

 

  • Big Data platform:  Do not look at Big Data as this mysterious beast that can solve world hunger!  It should be considered an additional data source which can augment existing data sources such as CRM, ERP or marketing automation data.  If you are a marketer, you should be connecting with your IT team to determine how to incorporate   this data into your existing data.
  • Analytics: Do not forget the analytics!  Discover, visualize and explore big data alongside traditional information to drive action and share your insights with others. Employ predictive analytics to identify patterns within the data leading to more accurate answers.
  • Answers!  Ultimately, it is what you do with the data versus the data itself! Use Big Data combined with traditional data sources to deliver more accurate answers by analyzing, predicting and automating decisions.

Connect with me to continue this discussion:  @BrendanRGrady

Would you have married your spouse if you only knew his or her address?

Marketers claim to know their customers because they have captured demographic and historical transaction information about them but would you have married your spouse based on age, height, address and the fact that they bought shoes once?  I think not.  Why should marketers think this enough to truly address the needs of today’s customers?

Many marketers are doing a very good job an incorporating traditional data critical to being able to target marketing efforts.

Data such as:

  • Self-declared demographic information
  • Marketing inquiries
  • Sales leads
  • Orders, payment history

This information is a great place to start.  There is no doubt that applying advanced analytics help marketers find patterns and trends while also predicting what is likely to happen next.  

Think about being on your first date with you spouse.  The conversation starts with the basics:

First Date

  • Where are you from?
  • Where do you live now?
  • Where did you study?

But quickly moves to:

  • What is your opinion of the President?
  • What do you do for fun?
  • What do you really dislike?

Now think about applying this in a business context.  As a marketer, I would like nothing more than to put an offer in front of customers and prospects that would not only speak to their business need but would also speak to personal likes.  How can you do this?

digital thumb print

Every interaction is an opportunity to get to know your buyers better.

Traditional interaction data from a marketing automation system such as Unica, Eloqua, Marketo or Neolane is a valuable source of information about  buyers’ behavior.  By capturing all interactions, regardless of channel, allows marketing organizations to apply predictive models to predict which customers are likely to respond to marketing offers via which channel and how frequently.    Using predictive models as part of a broader  customer analytics initiative helps marketing organizations identify which buyers to target and personalize offers for cross and up-sell opportunities

Great, we now know which offers my buyers will likely respond to and how frequently!  Now, go back to my first example – the date.  Getting to know your buyers personal preferences allows you to gain a deeper understanding of customer attitudes, preferences and opinions to make them part of the decision making process. Think about collecting customer opinions, attitudes and interest via surveys or data collection.  Use the interaction opportunity to capture a hobby or other personal activity.  Then apply this in your marketing activities.  If your buyer likes golf, find a way to incorporate it into your outreach (e.g. my marketing team has used direct mail/dimensional mailers giving away a free driver!).  

Social Media is another data source which can provide tremendous insight into customer opinions, both positive and negative.  Apply social media analytics to get the real opinion of your products to ultimately engage brand advocates and detractors in a conversation. CI Social media analytics allows organizations to capture consumer data from social media to understand attitudes, opinions and trends.

They key here is not to look at each of the pieces of data as stand alone pieces of information.  It is about combining them to get a “thumb print” which identifies the uniqueness of an individual.

Please feel free to connect with me on Twitter to discuss further @BrendanRGrady