Category Archives: Customer Analytics

10 steps to better B2B marketing – an analytics view

I am a marketer by trade.  I am feeling the tidal wave of change happening to our profession – Data, Cloud, and New ways of engaging with customer and companies are presenting us marketers with tremendous challenges but also tremendous opportunities.

The timeless responsibilities of marketers are changing.  For the longest time, we have been held to account for:

  • Know your customers:  Which segments are the most attractive?
  • Define what and how to market it:  Which products will penetrate a given segment leading to the highest amount of revenue?
  • Protect the brand promise:  How is your brand perceived in the market?

These responsibilities are morphing into a a set of new imperatives for marketers:

  • Understand your customers:  Even in B2B organizations,  marketers need to engage potential customers with individualized messaging and offers.   This is about understanding customer behaviors – what they do, have done and are likely to do.
  • Create a system of engagement:  No more “random acts of marketing”.  Establish a consistent process for engaging customers at every interaction point  – web, email, social, live event, communities.  The way you engage should be driven by analytics – what is working?  What is not?  What channels and offers should I be using?  How does my target audience like to interact with me?
  • Design your brand and culture so they are one:  Establish internal cultural norms that further your brand.  Culture will win out over brand every time. Ensure your brand is carried in a positive way in the market.

While these responsibilities and imperatives are important and need to be considered, they are not the end all be all.  In the end, marketers still need to find answers.  They need to be able to read customers expressions or body language in a world that has become increasingly digitized.

Here are some tips about how to go about this:

  • Capture all customer interactions:  Data collection is critical to meeting the demands of he segment of one.  Ask your customers for information which will uniquely identify them – e.g. email address;  BUT, offer them something in return – a white paper, a demo, attendance at webinar or event.  Ultimately you need to engage customers in a dialog across all channels.  Every interaction should be treated equally – events, web, email, social – all opportunities to capture a piece of customer info.
  • Categorize the different types of customer data:  Marketers need to understand the different type of customer data:  Descriptive:  Self identified industry, title etc; Attitudinal: Customer opinions, feelings and sentiment. Behavioral: Buying history, event attendance etc.. Interactions:  Website visits,  sales calls, email, social media etc..
  • Analyze all customer data in context: With  the data from point 3, look at all of these together to develop a “digital thumb print” of your contacts – the pattern that makes the contact unique.
  • Use various types of analytics:This is where a “one size fits all” approach does not work.  You need to apply the right type of analytics to the task:  data collection, social media analysis, social network analysis and sentiment analytics for attitudinal information; reporting, statistical analysis, data mining and  advanced visualization for descriptive, behavioral and transactional information
  • Predict client behavior:  Do not wait until something bad happens…predict what your clients are likely to do next.  Will you get it right all the time?  Nope, but you can be sure that the odds are in your favor to get it right if you are following steps 1 -5.
  • Create a closed loop and global view of the customer:  Steps 1- 6 must feed a cycle of marketing.  This is similar to the instructions on your shampoo bottle: Apply, rinse and repeat.
  • Make analytics available to all:  Access to information to make critical decisions cannot be given to the select few if you truly want to drive better outcomes via your marketing activities.  Insights must be available to every marketer when they need it and how they need it – via standardized reports, dashboards, analysis etc..
  • Gain “right time” intelligence:   So much is made of “real time”.  As a B2B marketer I laugh at this….I do not need real time analytics.  (Yes, I said it!).  Would I like it?  Of course I would, but I do not need it.  What I really need is insight at the “right time” – when the buyer is ready to act.  Understanding your buyers’ “thumb print” will allow you to identify that “right time” to put an offer in front of them.
  • Discover new business models:  With all of the data available to you and analytics to help interpret it, you may be sitting on a gold mine without even knowing it.

Truly understanding customers and what they will do next is not rocket science.  It require some critical thought and intestinal fortitude to let go of long held beliefs and believe the data.


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:

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