The power of providing value quickly

I want to share a short interaction that I had today. In marketing and SaaS there is a lot of talk about time-to-value. How long does it take for a potential customer to get value from your solution?

In a private slack community that I am active in, Michelle posted a frustration that she was having with Facebook data.

Years ago I presented at a conference hosted by IMPACT branding and got to meet Peter Caputa who was starting the company DataBox. In the years since the conference, Peter and I have been twitter friends. Through Peter’s tweets about growing DataBox, their client obsession, and, my usage of their product, I was familiar enough with how it worked. I made the comment with the link to Michelle for her to check it out.

60 minutes later. That is one hour. Michelle went from a business problem, to exploration of DataBox.com, starting a trial, connecting her accounts, and, finally to a solution.

How long in terms of time and steps does it take for a potential customer to learn what you have to offer, then get value from you? Is it 60 min? Why not?

Engaging the community to update the Marketing Technology Landscape (2020 update)

There are thousands of technologies and agencies participating in the marketing industry. Every year the team at Marketing Land compiles a giant list of companies and puts them into a PDF and Infographic.

Add/Edit/Delete

Trying to keep up with all the changes in the landscape is daunting and that is where the crowd comes in to help. As Scott Brinker says; “With the frothy M&A environment we’re in, we also miss mergers and acquisitions. We miss launches and pivots, where companies leap from one category to another. We miss name changes and logo changes (thank you, rebranders). And we miss the unfortunate endings of companies that drop into the martech deadpool.”

Martech 5000 from Marketing Land

Three ways to help

Contribute a new or updated martech vendor here.

Report an acquired or defunct martech vendor here.

Download the 2019 Excel spreadsheet here.

Let’s help get the landscape up to date

It is time for brands to take down content gates

It is 2020 and, this may be the year that click–walls come down. I was listening to Shep Hyken‘s podcast episode with David Meerman-Scott discussing David’s latest book, Fanocracy, when the subject of gating came up.

A little background on gating. Years ago, marketers were in a race to build big email lists. The plan was that once we got your email address, we could reach out to you directly and not have to pay ad rates to reach you. Then, with the rise of content marketing, gating became the main feature. Gating content would give you a straightforward metric, how many people filled in the form to read the article, infographic, white paper?

The evidence to tear down the gates is that according to David, a brand can see a 50 to 1 jump in content engagement by removing the friction. It makes sense; a brand creates content to inform new people about what the brand knows. It is the start of the relationship. When a brand uses gates, they are starting the connection with an ASK, give us your email, before we tell you anything. I have been a fan of David for years, and Fanocracy has a rising star co-author Reiko Scott.

It is one thing for David and Reiko to give a prominent brand example of removing the gate, increases engagement, and improves the relationship with the reader. Still, coincidentally Shep had run an A/B test of this concept with one of his white papers and found that the idea holds for small scale brands.

If you are twitter, make sure you give a shout-out to Shep Hyken, David Meerman Scott, and Reiko Scott.

The Related Impact of WEATHER on consumer purchases

An article from Sudipto Ghosh from Marketing Technology Insights is a great read on the efforts from AccuWeather to use their data to help inform brands. The premise is that weather has an effect on certain purchasing behaviors. Remember the “Gotta Get the Bread and Milk” video (LINK)? Using weather data to inform and adjust your advertising is now possible.

AccuWeatherIQ will help advertisers connect with U.S. users experiencing a variety of weather conditions today, tomorrow, or “next weekend” to provide effective messaging based on lifestyle activities and health management preferences influenced by the weather.

The company AccuWeather has a data product called AccuWeatherIQ that; “will help advertisers connect with U.S. users experiencing a variety of weather conditions today, tomorrow, or “next weekend”. The objective is to provide effective messaging based on lifestyle activities and health management preferences influenced by the weather.”

The company has partnered with Salesforce, LiveRamp and Beemray to support marketing efforts informed by their data.

AccuWeather was in the news recently… well the CEO was called out by John Oliver.

The show Last Week Tonight did a piece on AccuWeather (LINK) – but John Olivers position was on his oposition to the CEO of AccuWeather becoming the head of the government organization NOAA.

RELATED IMPACT: The connection here is obvious. Knowing that consumers behave differently in different weather conditions and being able to use the weather forecast to programaticly change your marketing should have a related impact. I will be watching as we head into winter storm season here in the New York area to see what changes in my ads.

Tough Competition for Customer Experience

Tonight I was reminded how tough the competition is for each account.  A friend of mine was clearly frustrated about something with his TMobile service and in 9 words vented his frustration.  Within 15min the competition was first to respond – offing to welcome him – 5 min after that TMobile responded.  How fast is your OODA loop?  In this case Verizon was able to get inside TMobile’s Loop. 

How fast is your OODA Loop?  OODA stands for Observe, Orient, Decide, Act.  The loop is because the process is repeated frequently.  It was created by military strategist, John Boyd and says that An entity (whether an individual or an organization) that can process this cycle quickly, observing and reacting to unfolding events more rapidly than an opponent can thereby “get inside” the opponent’s decision cycle and gain the advantage.  

“How fast is your OODA Loop? Well, that depends on several factors that can affect your reaction time. Simple Reaction Time is generally accepted to be around 220 milliseconds (Laming 1968) – (Source).  In marketing we have more time than 220 milliseconds, for this example the window for any Action was 15min.  

The Power of your Brand Defenders

In marketing we talk a lot about converting our customers to advocates.  The NPS score asks how likely a customer is to “recommend” a product or service to others.  We assume that this informs us on how well our brand is mentioned among private conversations.  I want to share an example that I came across today.  The image below is of a conversation that took place among dog walkers in my area.  

The conversation starts with someone that is unhappy with Nationwide Pet Insurance.  This customer feels cheated after paying for the insurance only to have it not cover them when they needed it.  This is not good for the Nationwide Pet Insurance brand.  Nationwide Pet Insurance was not tagged, and the company didn’t chime into the conversation.  This thread continued with customers questioning the value of Pet Insurance.  

Within one hour of the original post, someone that has a contrary and favorable experience with Nationwide Pet Insurance chimes in with her perspective.  “I have Nationwide for my dog and it has been great”.  One comment from a brand advocate changed the tone of the conversation.  

Brand advocates wield a lot power.  This is a good example of a brand conversation that took place without the brand’s involvement.  The advocates you create today will help you tomorrow.  

What are you doing with your brand to create Brand Defenders? 

Top 5 Powerful Analytics KPIs

Top 5 Powerful Analytics KPIs

    Key Performance Indicators are important, and particularly important when performing text analytics with survey data.  When conducting text analytics it is important to know which KPI metric you are interested in.  There are many outputs when conducting text analytics and it is imported to have the output in mind before you begin.  The output from text analytics can be a coded list of topics with the frequency counts.  If the data is from hotel customers you may want to know how often customers mention; linens, comfort, TV, and room service.  Another objective that uses the same hotel data could be to understand if mentions of room service have an impact on NPS ratings?  Yet another KPI could be revenue.  The objective might be to explore the relationship between mentions of room service and how much a customer spends at our hotel.  In this example you are using the revenue amount as your KPI.  In this post we will discuss the five powerful KPIs that we see used frequently when conducing text analytics.   

KPI #5 is Sentiment analysis  

    Sentiment looks at the words and compares them to an established dictionary for what words are positive, which words are negative and which are neutral.  When using Sentiment as your KPI the analysis is focused on uncovering which words, combination of words and which topics are increasing or decreasing sentiment and by what amount.  Sentiment is one of the most popular KPIs in text analytics because it can be conducted on almost all unstructured text.  This makes it useful on social media data where structured variables are limited and sentiment can be used to enrich other metrics such as percentage of mentions and reach.  

 

KPI #4 is Customer Satisfaction Score or CSAT

    CSAT is a broad term that describes many different types of customer service survey questions. The goal of any CSAT score is to measure a customer’s satisfaction level with your company.  The scale for measuring CSAT isn’t strictly defined.  Some have it on a 5 position scale ranging from very unsatisfied to very satisfied.  Others use a score that is derived from calculating the number of happy customers divided by the number of customers asked.  

 

KPI #3 is Customer Effort Score or CES Score

    Customer Effort Score is a metric to measure customer service satisfaction with one single question. The belief is that service organizations create loyal customers by reducing customer effort.

 

KPI #2 is Net Promoter Score  

    The NPS score was created by Satmetrix in 2003.  The NPS question is “How likely is it that you would recommend [company X] to a friend or colleague?” and the answer is offered as an 11 point scale.  When consumers answer zero through six they are considered detractors.  Customers that answer with a seven or eight are passive and those that answer nine or ten are the promoters.  In the HBR article The One Number You Need to Grow, “By concentrating solely on those most enthusiastic about their rental experience, the company could focus on a key driver of profitable growth: customers who not only return to rent again but also recommend Enterprise to their friends.”  According to NetPromoter.com (the website run by Satmetrix) “More than a decade after it transformed the business world, NPS® still stands alone as the only customer experience that predicts business growth.”

There are some that are critical of and question the predictability of NPS. “To this date there is not a sigle scientific (peer reviewed) study supporting that NPS predicts growth. The study that was used to launch NPS in HBR is also flawed (and HBR is not a peer reviewed magazine).” – Sven-Tore Bengtsson (Source: Link

    When using NPS as your KPI you can explore what topics are driving up or down your NPS score.  Using the output to focus the team on what areas of focus will have an impact on the score that matters to you.  

KPI #1 is Revenue

    The KPI that is most sought after is of course revenue.  It is the R in ROI and if your data can link customer comments to the amount of revenue that is generated by a customer than your text analytics will be able to provide insights into what is driving actual customer spending.  We have a case study example on OdinText.com (here is the link: ).  The case goes into detail on how Jiffy Lube was able to perform such an analysis in order to better understand which customer comment topics were driving revenue.  

Conclusion

When performing text analytics it is important to know which KPIs are available for you to include in your analysis.  

References: 

  1. Sentiment Analysis – https://en.wikipedia.org/wiki/Sentiment_analysis
  2. Mining the Web for Feelings, Not Facts – http://www.nytimes.com/2009/08/24/technology/internet/24emotion.html?_r=1