Book – The Analytical Marketer

Analytical-marketer.pngAn insightful book describes the process many companies in the industry undertake in some form – marketing transformation.  The book illustrates some aspects that many marketers observed in their organizations and some other changes that marketers expect to see in the future.

It was the first publication that discussed relationship between marketing and IT before discussing an infamous challenge of relationship between marketing and sales.  Our industry truly changed 🙂

The book suggests that modern business requires ‘fundamental shifts in the marketing organization itself: specifically, changes in the marketing mind-set, marketing structure, marketing telnet, and marketing leadership.”

An interesting aspect: customer journey includes acquisition and retention as equal parts.  Very often marketing view on buyer’s journey does not even include retention, or includes it as a little “box” on the right – an afterthought.  Another aspect of the journey – it is relatively simple.  Hopefully, we, as an industry, are moving away from a dozen of steps buyer’s journey that might contribute to over-complication of marketing initiatives.

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SAS had a traditional marketing organization – by channel.  The organization encouraged silos and channel-specific efforts, what was not effective. “There are even times when you can draw the wrong conclusions when you look at the performance of a channel independently.”

SAS reorganized to encourage collaboration between channels and created a new function of “orchestrator” who is “orchestrating” campaigns across all channels – digital, traditional, and emerging.

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New positions were created to help formalize partnership between marketing and IT, and also to strengthen the connection between marketing ans sales.

SAS is hiring more analytically-minded marketers in general.  By doing it, “you are not killing creativity or innovation, just seeking naturally curious employees with updated skills.”

An HBR interview and book overview – webinar.

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A few insights from the book:

  • Segmentation insight: SAS discovered that SMB targets responded better to general messages, rather than specific message for the segment.  Results improved when the SMB-specific campaign was closed and SMB segment added to the enterprise campaign.
  • Based on data (conversion and sales) one of long-standing PPC campaigns targeting expensive keywords was discontinued.
  • “Too often, organizations start chasing the next shiny object like social media before they have optimized everything they already have..”
  • “Data without use is overhead.”
  • “Make data quality everybody’s job.”
  • CXA – customer experience analytics (new for me term)
  • Interesting: in SAS shared services Nurturing is included into “Data Strategy” together with segmentation.

Sometimes our team needs to engage in shameless self-promotion.  We need to tell stories about the interesting things and projects the team is involved in to ensure that the rest of the organization understands our value.  We have to deliberately build credibility for marketing.

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Book – Big Data

big-data.pngThe book gives a good general introduction into the concept of Big Data and illustrates it with very interesting examples.  The examples show new business approaches possible in the world of Big Data, and how they are different from the traditional strategies.

Example 1: car manufacturer found an improperly working fuel gauge.  Normally, this discovery would start from a request to the gauge producer to solve the problem, what could affect new production.  car.pngHowever, the car manufacturer armed with data did not immediately informed the gauge producer, but created a software patch to correct the problem and sold it to the gauge producer.

Example 2: organizations use data tools to evaluate potential employees.  One organization discovered that graduates from top schools do not perform better than graduates from less prestigious educational institutions, as a result, personnel costs could be reduced with expectation of increased performance. In some jobs, employees with prior criminal record actually outperformed coworkers without criminal record.  Employees who used a non-standard browser were found more likely to take independent initiatives.

Important point: all data activities need to start from the strategy based on business need.  An average company won’t be able to understand and analyze all existing data – and it is not needed to run a successful business.  Only data relevant to a specific goal is required.

The SMART model — start with strategy, measure metrics and data, apply analytics, report results, transform your business — allows you to cut through the chaos.

Instead of starting with the data, start with your business objectives and what you are specifically trying to achieve. This will automatically point you towards questions that you need to answer, which will narrow data requirements into manageable areas.

Once you know what you are trying to achieve and you are clear on what SMART questions need to be answered, then work out how you can access that information so you can measure metrics and data.

The next step is to apply analytics, extracting useful insights from the data that can help you answer strategic questions. The data themselves are meaningless unless they help you to execute your strategy and improve performance.

Example 3: fashion retailer needed to understand who were its best customers.  The retailer measured foot traffic passing the store (mobile phone sensor), then combined this information with number of people coming into the store (the same sensor), and then combined it with actual purchases.  Result: window display could be optimized more effectively and one store was closed due to insufficient traffic.

Example 4: data aggregated from wearable devices became more valuable than the device itself.  Wearable device manufacturer re-imagined its business and became a data company, while still producing the device to collect data.

Important point: analytics and data visualization are part of the same task.  An idea that first data is analyzed, then visualized by a different group, and then presented to a decision maker would not provide the most value.  Analysis and visualization need to work together and the decision maker should not be expected to use visualization tools – but to receive the insight generated by the analysis.

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An interesting site mentioned in the book Information is Beautiful – the site highlights data visualization examples.

Love Your Pipeline Event

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Interesting: a panel of advanced industry marketers did not have significant experience in every industry area.  In many cases, they were starting ABM and just moving into predictive.  The shiniest of the shiny industry objects are new, and every marketing organization is trying to understand how to use the new opportunities for their business, or if these opportunities are beneficial for their business.

It was a pleasure to see “people” and “process” taking central stage in transformations of marketing organizations, and tools moving to the supporting side, where they belong 🙂

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Predictive technologies discussion:

“If you don’t have right people, don’t just buy the tools.  You won’t get enough benefit out of the tools…”

Another interesting perspective: improvement takes time…  and, in many cases, years.  (Very good visualization of “marketing improvement” from Insight)

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Predictive technologies discussion:

“We just put some tools in.  In 6 months we will see data…”

Surprising: sales aspect of ABM may not be entirely positive. Sales might feel threatened by account-based approach: “Now they will give me a limited number of accounts and I can not go outside the list…”

Tools mentioned during the event:

Gecoboard  – a tool that allows visualizing and easily exposing data in the office.  The board integrates with a variety of apps (including SFDC, Google Analytics, Excel).

“Live TV Dashboard that improves key business metrics”

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Conversica – a “sales assistant” AI, that communicates with prospects, warms leads and sends them to sales.

The tool has a free trial limited to 25 leads, and not limited in time…

Book – The Business Blockchain

blockchain.pngThe book is a good introduction to the industry concepts.  Blockchain often perceived as a technology only without understanding of other aspects of the phenomenon.

What is the blockchain?

Blockchains are new technology layers that rewire the Internet and threaten to side-step older legacy constructs and centrally served businesses. At its core, a blockchain injects trust into the network, cutting off some intermediaries from serving that function and creatively disrupting how they operate.

Blockchain has technology, business, and legal aspect.  It is a mechanism that allows transactions (and currencies) without a need of trusted central authority.

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As blockchain has three different aspects, it can potentially bring change and innovation into technology, business, and also legal establishment.  From another side, blockchain faces obstacles to overcome in all three fields (technical nuances, business processes, and local laws).  It will be interesting to watch how blockchain will evolve and which aspects will be more critical for wider adoption.