People-to-people Marketing and “Small Data”

Actionable marketing strategies come from looking at the “small data” sets and applying human insight.

Actionable marketing strategies come from looking at the “small data” sets and applying human insight.

Human insight combined with “Small Data” provides a better customer experience

Devin Wenig, President of eBay Marketplaces recently spoke with McKinsey & Company about how digital technology was transforming the retail marketplace. One of his insights that can apply to companies serving the aviation industry was his take on the importance of “small data” vs. “big data”.

For definition purposes, let’s identify “big data” as data sets that represent large groups of people and certain types of behavior associated with their purchasing habits. This data is gathered from transactional data, website analytics and social insights, and usually requires the service of a data scientist to interpret trends and connections.

“Small Data,” on the other hand, is about putting the customer first. Engaging the customer with information and tools organized and packaged to be easily accessible, understandable, and actionable to accomplish the task at hand (think apps). Companies that understand small data can use it to their advantage by creating relationships leading to increased brand loyalty and repeat business.

“Small Data” leads to actionable strategies

Actionable marketing strategies come from looking at the “small data” sets and applying human insight, resulting in knowing your customer base as individuals – their likes, dislikes, purchasing history – and providing an easy to use, relevant online user experience.

Long tail data – a complete customer picture

A search engine can sort through millions of bits of data from a keyword query and provide an exact match, but it cannot provide additional queries for items that may be related. For example, say your website has a search feature and the customer has entered a part number. The part number query will take them to the requested part configuration but is incapable of identifying additional parts that may be needed for installation in a specific airframe or for a retrofit of a new digital component. Using the “small data” approach, the search query could also display a complete view of additional components associated with the original query, assuring that the customer gets all they need the first time around.

Relevant online experiences lead to loyal customers

People-to-people marketing requires engaging with customers by providing useful information. Thinking beyond a single data set and applying insight such as including installation tips and additional component selections creates customer loyalty. Thinking of “small data” as the “right data” will help marketers build better customer profiles, leading to a better online experience for all involved.

Additional articles you may find of interest on this topic:

Is your website attracting customers or sending them away?

Using social media to gain customer insight.

B-to-B social media strategy: Quality not Quantity

Please leave your comments or thoughts below.

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The challenges of “Big Data”

Don’t be a slave to the data; rather, use it as a tool to sharpen the creative solution

Don’t be a slave to the data; rather, use it as a tool to sharpen the creative solution

Big Data is a tool and should be used as a means to an end

“Big Data” is a misleading term. It’s not a technology, but rather involves using data to gain insight. Big Data helps you visualize structured, semi-structured, and unstructured data. This visualization of combined data provides a multi-dimensional view of the ecosystem your product or service resides in.

Types of data

Structured data, also known as Business Intelligence (BI), is transactional data.  Examples include addresses, SIC codes, point-of- sale data, customer resource management data, phone numbers, emails, loyalty card use, and energy consumption data. Data of this nature can be accessed and viewed in Excel spreadsheets.

Semi-structured data consists of web server click stream data, such ad web logs, IP addresses, page visits, time on page, cookie tracking, geo-usage patterns, customer behavior while on site, and the development of user profiles. The primary characteristic of this type of data is that it does not lend itself to display in rows, columns, or text.

Unstructured data is the content of documents, natural language, Tweets, Likes, comments, blogs, phone calls, emails, audio files, and images. These are the elements of human communication recognized as content but completely foreign to machine language.

How to use the data “Big Data” provides

From a marketing perspective, Big Data can be viewed as three segments:

1. Big Data when viewed properly can provide better insight

This was once the domain of a “gut feel.” Now when combining the three aforementioned data types, a panoramic view can be created of the acceptance and use of the product or service.

2. Better insight helps in making better business decisions

All of this data crunching provides a granular to global view of the acceptance of your product or service offering.  It is in this context that better business decisions can be made with regards to where to geographically expand, identify the most desirable product features and attributes, and which marketing efforts are delivering the anticipated results.

3. Better business decisions lead to better creative solutions

Big Data, when represented properly, can complement a creative brief by acting as a wall of information that can be prioritized, moved, and reconfigured for actionable items and measured for results.

“Big Data” challenges

Don’t be a slave to the data; rather, use it as a tool to sharpen the creative solution, extend the brand engagement, and think beyond the current place in time that the visualization represents.

In addition, be aware that small brands may find the results disappointing because of an insufficient amount of semi-structured and unstructured data that is available.

And finally, management has to be committed to Big Data by providing resources and direction. Big Data offers marketing accountability, but it is incumbent on management to decide the following:

  • What to measure
  • What data has the highest priority to aid in business decisions
  • Where to invest resource and capital
  • What to do with the data – how does it shape the business outcome

Additional articles you may find of interest on this topic:

Big brother and marketing ROI

Big data and creativity

How to build a connected brand

Please leave your comments or thoughts below.
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Why ROI measurement for inbound marketing fails

ROI measurement fails to consider the shelf life of inbound marketing content

ROI measurement fails to consider the shelf life of inbound marketing content

Simple ROI measurement for inbound marketing fail to consider the shelf life of content

Here we are in the age of “Big Data” where everything can be tracked and scrutinized. For aviation marketers is means one more hurtle to jump when trying to justify investment of marketing funds for inbound marketing programs.

Traditional RIO measurement seems very simple – take the gain of the investment, subtract the cost of the investment, and divide the total by the cost of the investment.

ROI = (Gains-Cost)/Cost

This simple calculation comes up short in several areas:

  • How can you determine the value of a follower?
  • What’s the value of a blog response?
  • Is the content presented in such a way that it has an evergreen shelf life?

The value of a follower

What is a follower of your inbound marketing worth? Monetizing the value of a follower is subjective because we get into grey areas of determining worth. Does the content present the social face of the corporation? If so what is the value of good will towards the corporation? Does the follower reference the content in their social media network? If so, how do you calculate the value of reach from linked content?

Content shelf life

I like to think of inbound marketing content- blogs, white papers, e-books, videos and infographics as a conduit that provides a way to gain insight into the brand.  Produced correctly the content can influence purchasing behavior and have a very long shelf life.  This also throws a wrench in the traditional ROI measurement because the cost of producing the content needs to be measured over the time that the content remains relevant. For example, a video is produced about a new avionics component. The marketing expense to produce the video was $10,000. The video is placed on the corporate website and syndicated on various video sharing sites.  First year sales for the new component were $100,000 with gross profit of $40,000.

Traditional ROI measurement would look like this.

ROI = ($40,000 – $10,000)/$10,000 = 300% ROI

Now consider year two of the video investment with component gross profit of $30,000 and a marketing expense of $1,500 for website maintenance and syndication cost.

ROI =($30,000 – $1,500)/$1,500 = 1900% ROI

Inbound marketing measurement – ROI or VOI (Value of Investment)

As the examples above show ROI measurement can be can be modified to suit the situation -it all depends on what you include as returns and costs. Granted this a very simplistic view of ROI and there are more robust financial models available. That said, I’d recommend that a more accurate measurement: VOI = (Value-Cost)/Time

Another way to look at value of investment would be not to invest at all

This is another approach to determine the value of content. The internet is a crowed place with brands fighting for the attention of an over caffeinated, 140-character challenged audience. Their purchasing decision is neither entirely rational nor based on the lowest price. It can be influenced by website functionality, peer reviews, blogs, leadership papers and content that helps them select the product that is best suited to their need. If the brand is not active in this environment then it virtually invites the competition to gain the share-of-voice and increased exposure.

Additional Articles on this topic you may find of interest.

Big data and creativity

Big brother and marketing ROI

Why content development will drive the future of aviation marketing

Measuring Digital Display Advertising ROI

Please leave your comments or thoughts below.

Aviation Marketing: Big data and creativity

Creativity needs big data to define the landscape in which the brand operates

Creativity needs big data to define the landscape in which the brand operates

One provides tactical insight, the other the emotional glue

Big data is the buzzword of the day. The techno savvy number crunchers are heralding big data as an “end all, be all” for tracking RIO and determining which marketing initiatives to fund. I’m in agreement that big data, when properly interpreted, can provide customer insight as to the purchasing habits and the media channel that culminated the sale. No argument – this is valid tactical information and should be considered when planning marketing initiatives.

Big data has limitations

Big data interpretation is also influenced by what the interpreter wants from it. We all know numbers can be twisted to justify decisions based on the interpreter’s bias and ultimate goal.

Big data also presents a one-sided view of the transaction process. Yes, it can isolate the channel that the purchase was transacted through, but it cannot measure the cumulative effect of brand value and preference across all the marketing channels that led to the conversion.

Big data lacks soul

Dissecting any purchasing process has to take into account the emotional decision to consider the brand in the first place. This is where big data comes up short.

Purchasing decisions start by pinging an emotional need.  These emotions are what make us human and drive our wants, desires, and needs. Emotions are the glue that create an attachment to a brand and pique our curiosity to investigate features and benefits to justify the purchase.

Creativity needs big data and visa-versa

Big data is automated. It’s a logical path that turns creativity into a commodity. From automated ad purchasing programs to social media sentiment, tracking these algorithms can not detect sarcasm, joy, empathy or any of the other emotions we humans employ on a daily basis to communicate, cope, and justify our purchasing decisions.

There was once a time when creativity was celebrated. Good advertising built brands and created brand preference. It could sweep the nation with catch phrases and imprint the brand message in the minds of millions of potential customers.

Creativity needs big data to define the landscape in which the brand operates. Big data can help creative thinking by providing comparative analysis, insight into purchasing habits, and models of what not to do based on different scenarios.  Ultimately, this tactical execution may be big data’s greatest contribution to the creative process.

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