Tag Archives: Big Data

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.

Analytics is not a thing you “do”…it’s a way of life.

I recently attended conference in Singapore

A beautiful view of Singapore at night.
A beautiful view of Singapore at night.

where I had the chance to listen to thought leaders discuss the need for analytics to address what Gartner refers to as the “nexus of forces” – CloudSocialMobile and Information.   Mychelle Mollot took a deeper dive on the “information”  force in the Big Data and Analytics keynote.

As a marketer I grapple with explaining these nexus of forces and the need for Big Data and Analytics everyday.  Everyone seems to have an opinion on exactly what Big Data is and why it is so important.   It was in fact several customers and partners  who reminded me of several things: Continue reading Analytics is not a thing you “do”…it’s a way of life.

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:

Finally! Predictive Analytics even I can use!

When I was running marketing operations, I had hired a statistics expert to come into the organization to help me make sense of all of our marketing data.  As I worked with this excellent “stats guy”, I realized that predictive analytics can be pretty darn complicated and required a more specialized skill set than I had originally thought.

This all changed on Tuesday June 11, 2013.  IBM announced the availability of IBM SPSS Analytic Catalyst – a statistician in the software – which makes predictive analytics on big data available to mere mortals like myself.  I was admittedly skeptical that this new offering could actual make predictive analytics accessible.  There had to be some gotcha….  well, I was wrong (not something I admit often!).

So, what does this thing do exactly? Let’s say you are a marketer and want to understand which customers would likely “churn” or leave for your competitor.  This is where Analytic Catalyst comes in.  There is a three step process to get the answers you need.

  1. Add your data (csv file)
  2. Select the field you would like to predict
  3. Review plain English results

Sounds simple?  Well it is.  Review a demo here to see how this can help marketers, customer service teams, sales and other organizations find the small data within the big data!

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