Explore the Four Levels of Text Analytics

Explore the Four Levels of Text Analytics

NPS BASICS AND BEYOND
Explore the Four Levels of Text Analytics
Text Analytics

Explore the Four Levels
of Text Analytics

key takeaway

Get more insight into your NPS data with text analytics. Know what’s possible using software that supplements human expertise.

Best Practice

We suggest using text analytics software to screen customers’ answers to the open questions in your surveys, then letting humans make the final decisions about priorities.

Here are the four levels of text analytics that we recognize:

  • Single word concepts are often shown as word clouds and are marginally useful. Yes, your customer talked about ‘service’ a lot, but was it good service or bad service? And what service are they referring to? ‘Service’, ‘Services’, and ‘Support’ will appear as separate items.
  • The addition of basic language structure recognition provides multi-word concepts such as ‘Deluxe hamburger’ and ‘high-end burger.’ Note that these will be shown as different topics.
  • The next level adds sentiment into the equation. The multi-word concept is qualified in some way, usually in terms of positive or negative sentiment We start to see themes, usually grouped in terms of what customers liked and did not like. ‘The air conditioning was too cold’, and ‘The whole family was freezing’ would appear on a long list of themes with negative sentiment but would not be grouped together.
  • The addition of a taxonomy gets to the heart of Natural Language Processing. This allows the grouping of topics that mean the same thing but use completely different words. ‘The clown frightened the children’ and ‘The main act was unsuitable for young people’ would be grouped together, as the software will recognize that they probably mean the same thing.

It’s a sophisticated area. Many software providers will produce a free analysis for you. We suggest providing them with the largest file of open text responses you have and comparing what they can do with them.

go beyond basic nps analytics

Just as you can only act on what you know, you can only analyze the data you have. Even the most comprehensive, multi-part attitudinal data will only ever cover a fraction of your customer base. Visionary programs use analytics that incorporate machine learning to transform operational data into customer insights, with attitudinal data as a critical tool for calibration. To get there, download our guide, take our comprehensive training course, or read about the future of NPS.

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS
Manifesto

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS Manifesto

ABOUT OCX COGNITION

OCX Cognition delivers the future of NPS. We ensure customer experience success by combining technology and data science with programmatic consulting. In our Insights section, we present a comprehensive and evolving collection of resources based on our research and expertise, collected for CX leaders committed to delivering business outcomes.

Explore the Four Levels of Text Analytics

Turning NPS Data to NPS Insights You Can Use

NPS BASICS AND BEYOND
Turning NPS Data to NPS Insights You Can Use
Actionable NPS Insights

Turning NPS Data to
NPS Insights You Can Use

key takeaway

Actionable NPS insights are a step up from NPS data, and getting there requires excellent analytics. Simple reports on CX performance are not enough to illuminate the elements of customer experience need to be prioritized for improvement.

Best Practice

NPS data is just data until you use analytics to transform data to insight. Prioritize making your insights actionable so that you can do what matters: improve the customer experience.

A critical step in making sense of customer feedback is identifying where to focus when it comes to enacting change. Unfortunately, we see many companies continue to report NPS and even set NPS targets without identifying and acting upon specific improvements that will impact NPS. Vague platitudes such as “Put the Customer First”, while good for increasing organizational awareness, do little to direct decision making.

Analysis of data tied to journey drivers will yield the greatest insights, particularly when operational and financial data sources are integrated with your survey data. Analytic tools range from basic correlation to sophisticated AI models, with the level of sophistication mirroring the depth of your insights, from a retrospective view indicating what happened to a forward-looking view of what will happen.

If you are new to CX survey analytics here are some helpful guidelines:

  • Begin by examining components of the overall customer journey in terms of correlation to NPS.
  • Look for differences in the journey experience by NPS category – Promoter, Passive, Detractor.
  • Look for differences in the journey experience by key customer segments.
  • Identify “moments of truth” along the customer journey, meaning those interactions where the experience is highly correlated to likelihood to recommend.
  • Sharpen your understanding of which variables have the greatest impact by applying regression (the impact of a change in one or more variables on NPS) or relative impact analysis (the impact of each individual independent variable in relation to all variables on NPS)
  • Gain additional perspective by analyzing open comment text by theme and sentiment. Text analysis provides an additional perspective on customers’ top of mind thoughts and sometimes yields interesting competitive learnings. However, even when volume by category is high, text analytics is more limited than quantitative analytics when it comes to understanding how impactful the issue is.
  • Prioritize 1-2 moments of truth seen in high value segments for action planning

The steps above can provide valuable insights from your survey data determining what matters most to your customers NPS performance. However, organizations today need insights on the experience of all customers. You need to predict what your customers will do in order to make better business decisions. This link can now be made through a predictive model, Spectrum AI.

When building a predictive model, the underlying data sources are key. Relying solely on survey data is inadequate as it represents a small portion of your customers base and becomes less relevant rather quickly due its periodic nature.

To achieve next level insight companies are expanding the data sphere beyond survey feedback to include operational KPIs and financial data. Machine learning and predictive analytics are applied to this richer data set to deliver Spectrum NPS, an evolved, better NPS which is enabling organizations to make even better decisions in real time, ultimately delivering transformative business outcomes.

go beyond basic nps analytics

Just as you can only act on what you know, you can only analyze the data you have. Even the most comprehensive, multi-part attitudinal data will only ever cover a fraction of your customer base. Visionary programs use analytics that incorporate machine learning to transform operational data into customer insights, with attitudinal data as a critical tool for calibration. To get there, download our guide, take our comprehensive training course, or read about the future of NPS.

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS
Manifesto

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS Manifesto

ABOUT OCX COGNITION

OCX Cognition delivers the future of NPS. We ensure customer experience success by combining technology and data science with programmatic consulting. In our Insights section, we present a comprehensive and evolving collection of resources based on our research and expertise, collected for CX leaders committed to delivering business outcomes.

Explore the Four Levels of Text Analytics

NPS Data from Repeat Responders Delivers Unique Insights

NPS BASICS AND BEYOND
NPS Data from Repeat Responders Delivers Unique Insights
Repeat Responder Analysis

NPS Data from Repeat Responders
Delivers Unique Insights

key takeaway

To verify NPS data validity, data from repeat responders is an important tool. A comparable, representative sample of your customers from period to period increases confidence that any change in NPS is real.

Best Practice

There are two approaches to comparing repeat responder data. The most common approach, which can be used in both B2B and B2C, is to compare the NPS of individuals who have responded in both the current period and the previous period. At a high level you will want to check the trend of the group NPS to see if the change in repeat responders’ score algins with the change seen for all respondents. If the trends are similar it reinforces that the change you are seeing overall is real.

The next level analytics is tracking how individual loyalty may have shifted period to period. For simplicity’s sake we recommend you do this using the NPS categories – Promoter, Passive, Detractor. A helpful way to visualize this is an Alluvial Diagram, which shows the flow and change in proportion from one period to another. The change in repeat responder group NPS is indicated at the bottom while the shift in categories over time is highlighted by the colored bands. The thickness of the band represents the volume. A deep dive into understanding what’s behind the shifts will determine your goals by category: recover, grow, evolve.

Another, quite similar, approach can be used in B2B. As the true indicator of loyalty for an account is the unit rather than an individual, analyzing repeat account NPS can be even more effective. The caveat here is that you have an adequate number of respondents per account. We recommend at least 3 respondents per account for each period.

Here are some guidelines for determining whether an account is overall Promoter, Passive or Detractor.

  • If there are more Promoters than Detractors in the account, it’s a Promoter
  • If there are more Detractors, it’s a Detractor
  • If there is the same number of Promoters and Detractors, it’s a Passive.

As you start linking operational data to your serial Detractors and staunch Promoters you will be better positioned to develop a customer strategy that delivers revenue growth.

go beyond basic nps   analytics

Just as you can only act on what you know, you can only analyze the data you have. Even the most comprehensive, multi-part attitudinal data will only ever cover a fraction of your customer base. Visionary programs use analytics that incorporate machine learning to transform operational data into customer insights, with attitudinal data as a critical tool for calibration. To get there, download our guide, take our comprehensive training course, or read about the future of NPS.

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS
Manifesto

REPORT

The Complete Guide to NPS Basics and Beyond

TRAINING

Leading an Outcome- Oriented
CX Program

REPORT

The New NPS Manifesto

ABOUT OCX COGNITION

OCX Cognition delivers the future of NPS. We ensure customer experience success by combining technology and data science with programmatic consulting. In our Insights section, we present a comprehensive and evolving collection of resources based on our research and expertise, collected for CX leaders committed to delivering business outcomes.