Post-Purchase Rationalization

[Vishwadeep Khatri]

Q 698. In the context of Lean Six Sigma, how does 'Post-Purchase Rationalization' skew customer satisfaction metrics? Are there any analytical methods to identify and rectify its impact?

 

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[Akkul Dhand]

Post-purchase rationalization is a type of cognitive bias where someone who has purchased an expensive product or service overlooks any faults or defects in order to justify their decision and maintain a positive self-image about their choices.

It is also known as 'Buyers Stockholm Syndrome' because the buyer develops a psychological attachment to the product, similar to how hostages develop a bond with their captors in the Stockholm syndrome, or 'Choice-supportive Bias' which is a tendency to retroactively ascribe positive attributes to a selected option.

For Example; if someone buys an expensive gadget that doesn't live up to their expectations, they may focus on the features that they like and dismiss any flaws to feel better about their decision of purchasing the gadget. This also helps in reducing cognitive dissonance, or mental discomfort they might feel about the decision.

Effect on Customer Satisfaction Metrics

 

In the context of Lean Six Sigma, post-purchase rationalization can significantly contribute to skewed customer satisfaction metrics by portraying misleading impressions of how satisfied customers truly are with a product or service. Here's how it may affect the data,

1. Inflated Satisfaction Scores: Customers experiencing post-purchase rationalization may report higher satisfaction levels than they actually feel, by downplaying any dissatisfaction they may have. This can lead to inflated satisfaction scores, making it seem that the product or service is performing better than it really is.
2. Biased Feedback: When customers rationalize their purchase, and provide overly positive feedback, this can distort the voice of the customer, making it harder to identify areas of improvement.
3. Masking Underlying Issues leading to missed improvement opportunities: Lean Six Sigma relies on data to identify defects and opportunities for improvement. If post-purchase rationalization causes underreported problems or overemphasized positives, it can lead to missed opportunities for improving the product or service.
4. Misleading Loyalty metrics: Customers who rationalize their purchases are more likely to exhibit wavering loyalty over time, even when satisfaction scores in the short-term remain high.

 

Identifying post-purchase rationalization

1. Longitudinal Analysis: Tracking satisfaction metrics over a longer time period to see if their is a decline after the initial purchase. This indicates rationalization.
2. Customer Journey Mapping: Comparing pre-purchase expectations with post purchase satisfaction to spot gaps and rationalization.
3. Sentiment Analysis: Utilize sentiment analysis through social media mentions and online customer reviews can uncover how customers feel about their purchases and analyse open-ended feedback to inconsistencies between the same.
4. Behavioural Analysis: Customer behaviours, such as return rates and post-purchase engagement can provide insights into the effectiveness of rationalization. High return rates or low engagement may suggest that customers are not satisfied despite their rationalizations.

 

Additional Strategies to Rectify Post-purchase Rationalization
 

1. Encourage transparent information relay in your communications and product information and communicate the value of honest feedback so the customers feel more informed and less likely to rationalize poor experiences.
2. Monitor behavioral data such as tracking returns, product usage where possible to adjust your understanding of customer satisfaction. Repeat purchases is another metric that can be tracked to understand customer behavior.

 

In conclusion, post-purchase rationalization can distort customer satisfaction metrics by causing customers to overlook flaws in a product or a service and report inflated satisfaction. This bias can lead to missed improvement opportunities as well as inaccurate data. To address this, businesses can analyse customer behaviours over longer time periods, engage in sentiment analysis and encourage true feedback to gain a clarity on their customer satisfaction scores.

[Deep Dave]

Post-Purchase Rationalization occurs when customers convince themselves that their purchase decision was the right one, even if they are not completely satisfied. This can distort customer satisfaction metrics / KANO model in Lean Six Sigma projects, leading to misleading conclusions about a product or service's quality.

 

For instance, consider a scenario where a company introduces a new product, and customers who spent a significant amount on it might report being satisfied to avoid feeling regret, even if the product didn't fully meet his expectations. This can result in misleading satisfaction scores, preventing the identification of genuine improvement needs.

 

Analytical Methods to Identify and Rectify the Impact:

 

1. Behavioral Analysis: Off course in above cases customer may not repeat purchase, so tracking a metric of "repeat purchase" will give more insights. In addition, we can track metrics like return rates and complaint frequencies.

 

2. Drafting Better Customer Feedback Survey Questions: Sometimes survey is designed in such a way that we get the best CSAT score, instead we can design precise surveys asking about specific aspects or features of the product.

 

3. Surveys At Right Time: May be not at the time of purchase but if we take survey somewhat later during product lifecycle where customer has long exposure of products or services then may be real CSAT score will come out with actual concerns.

 

4. Net Promoter Score (NPS): May be at the time of purchase the customer gives good CSAT score due to this phenomenon, but in this case if customer is actually not satisfied, he will not recommend this product or service to others, so yes NPS can be another metric to check!

 

5. Comparative Analysis with Competitors: Benchmarking with features provided by other best product/service providers may help offset this phenomenon.

 

By using these methods, Lean Six Sigma teams can better detect and address the effects of post-purchase rationalization.

 

 

[Mohammad Riyadh Al Kamal]

In the context of Lean Six Sigma, how does 'Post-Purchase Rationalization' skew customer satisfaction metrics?

 

There are occasions when customers buy something and later on, try to justify their purchases through overlooking the shortcoming of the product already known to them. This may happen on account of impulsive purchases, any purchase beyond affordability, any purchase made based on commitment to a brand (inflated perception) rising out of groupthink etc. This phenomena or bias is called Post Purchase Rationalization or PPR.

PPR may hinder customers from acknowledging or communicating any issues or shortcomings they encounter with the purchased offering, impeding the resolution of concerns and ultimately impacting customer satisfaction levels. From Six Sigma context, this would skew the VOC and may result in identification of a CTQ which is not a priority at all. Subsequent QFD matrix would also be faulty.

 

Are there any analytical methods to identify and rectify its impact?

 

Identification:

There are different ways to identify PPR as outlined below (not exhaustive)

1.       Qualitative research methods like surveys, interviews, focus group discussions etc. may bring out the true reasons behind satisfaction and dissatisfaction. The output of the research need to identify PPR

2.       Gap analysis between Customer satisfaction score and Measurement like net promoter score, repeat purchase, customer loyalty etc. can be done to identify discrepancy. Major discrepancy would indicate PPR.

3.       Benchmarking with competitors in the industry may identify weaknesses in product and may contradict customer satisfaction score. Any discrepancy would indicate PPR

4.       Analysis of Customer behaviors like online reviews, returns, exchanges can help identify discrepancies with satisfaction score & indicate PPR

 

Rectification

1.       Post identification of PPR using above methods, necessary Six sigma processes can be taken up to remove the pain points, defects etc. at pre-delivery stage so that future satisfaction score matches the expectations

2.       Extensive post-purchase communication with customer needs to happen to understand the pain points & take necessary mitigating steps i.e., discount of future purchase, service discount etc.

[Puneet Vohra]

Post Purchase Rationalization:

 

When we purchase any object or service and somewhat compromises with the expectations that we had in our mind. And repeats in our sub- conscious mind that I chosen the good product or service that leads to unrealistic satisfaction scores and misleads in lean six six sigma world with less scope of improvements.

 

How does it skew the CSAT metrics:

 

Misleads the NPS(Net promoter score)- The PPR might give high loyalty data which directly fools the customer by shown by showing more loyal than they actually are.

 

Biased Feedback: Customers might not mention any issues leading to any feedback to that doesn't show where improvements are required.

 

High CSAT numbers: Customer may be giving higher ratings hiding their preconceived notions  which makes a product or service look better than it is.

 

Analytical methods to find PPR:

• Getting the surveys done frequently might be monthly, quarterly etc.
• Analyse the behaviour of those customer s and investigate their buying patterns also
• Keep an eye those customers as well who mention any specific problem but still rates the services high must be doing rationalization
• A review which is mentioned with good words but has a negative sentiment score might lead to PPR
• If any service or product having any flaw still it sells like heavily, could indicate to PPR

 

[Rohit_Kurup]

Post purchase rationalization, a variety of Confirmation bias is the rationalization done for supporting a decision which has already been taken ignoring all sorts of scientific or logical reasoning and ignoring new information. This is also something which also leads to a lot of the highly irrational voting patterns, irrational practices, lifestyle choices, purchasing decisions, selection of route maps, etc.

 

A lot of people postpone healthy habits rationalizing their current lifestyle (which as per experts is not good enough) as being sufficient and that they have plenty of time to implement healthy habits later.

 

One another example is how decisions on AI generated answers and Plagiarism tests are conducted using AI and algorithm tools to identify Plagiarism and algorithm-based AI content identifiers may erroneously mark formally-worded, neutral-3rd-person-language and grammatically-correct human created texts to be marked as AI created. Here also the fact that a human created content from someone who has observed how professionally written reports are worded, will be marked as failing AI tests.. Thus, necessitating changing a practice of formal writing to writing answers in a more informal tone and addition of images and emojis to pass these tests.

 

 

Analytical Methods to identify and rectify it are: -

1. Pattern Identification through Blind testing (kind of similar to Measurement System Analysis): - Identifying whether feedback for products/services/experiences are being repeated post anonymization of the same.

Considering that post purchase rationalization is primarily a folly of the human mind. Examples of these can be seen in organizations with a strong push for Diversity, Equity and Inclusion have anonymized resumes being viewed by hiring managers in order to avoid confirmation bias. Similarly, Social media platforms such as YouTube is awash with a lot of experiments where people when asked to use products, services or even while discussing ideas share very different feedback and are either stumped or try to change back their feedback.

 

2. Critical Evaluation

Critically evaluation post the purchase can lead to coming to the right analysis but can also lead to buyer's remorse. Wherein again the feedback may come from the fear of a wrong decision being made. This can be avoided by systematically using Business Modelling techniques such as Monte-Carlo simulation and group decisions/strategy frameworks Analytical Hierarchial Processes. These are useful tools to carefully analyse the data and address biases of any sorts.

 

3. Constant Vigil/Situational Awareness/Retraining

Constant vigil/mindfulness/situational awareness are certain skills which are developed through much practice in order to catch oneself from being complacent and falling to certain biases. 

In some of the organizations attempts to address such types of biases have been successful through regular training and awareness campaigns.

 

[Indrani Ghosh Dastidar]

‘Post – Purchase Rationalization’ is also considered as “Cognitive Bias”, it generally can observe after a purchase. When someone buys a product, then the buyer tries to look for the justify the choice even if that is a impulsive buy.  By rationalizing purchase individual seek to align their actions with their self-esteem.

 

In context of Lean Six Sigma, if we want to gather customer feedback regarding Post- Purchase Rationalization, there is a possibility that the customer satisfaction score is skewed. Reasons :

• Customer Bias may play a role while providing the survey, it may inflate the data, hence will show false positive value
• If the survey is based on cognitive bias then it may result in mislead the data, hence it would be challenging to identify the opportunities of improvement

To understand the if the collected data is inflated by 'Post-Purchase Rationalization' , we can go with KANO workshop which is a method to collect Voice of Customer. Where we can try to understand the parameters ‘Basic must have’, ‘More the better’ & ‘Delighter’ based on the responses received in each segment we can reassess the collected feedback & can try to eliminate the biased feedback.

[Anchal Parashar]

In generic terms, justification of the factors which lead to a purchase decision for certain product or service, but found to be untrue later, can be bracketed as 'Post Purchase rationalization' phenomenon or behavior.

 

It triggers because the Purchaser or Customer try to prove the correctness of their decision, no matter, how illogical it may sound in reality. Every effort is made to ignore the actual positive aspects for the service and appreciate the aspects basis which decision has been made for purchase

This phenomenon greatly impacts the Customer Satisfaction Metrics like C-SAT & NPS. Data collected from the customers for aforementioned metrics won't be accurate, as it is shared with an intent of proving their decision. And when such data is led down to draw a histogram basis the responses collected, it would be more positively skewed, which may lead to flawed business strategy making for the entity collecting the data. Also a ripple effect would be felt on the entire supply chain !!!

 

Various logical methods can be deployed to counter Post Purchase Rationalization effects on Customer Metrics as listed below,

 

- Time of Data Collection : Avoid collecting data during festive or holiday season, as purchases made during this time could be of impulsive nature, which means customer may not weigh various factors of product while making a purchase

 

- Segregated Data Collection: Collect data at equal time intervals during a particular cycle. This will help in touching all purchasing behavioral patterns which varies with time

 

- Improvised Customer Connects - Deploy structured ways to reach to customers on regular basis to make them understand about the product or service, which will help them to make informed decisions, which will eventually enhance the data quality at the time for actual collection

[Suraj Prasad]

What is Post-Purchase Rationalization?
The biasedness of remembering the positive aspects of a buyers decision and associate mostly the negative aspects/features to the negative decision.
Taking an example of the online buying, customer are likely to provide more positive reviews of the  products they have bought and remember only the negative features of the products. This create a skewness in the customer satisfaction reviews and products is most likely to get more positive review or star ratings. The product may end of showing more positive review and feedback than another product. This may not be the true comparison of the chosen product and features with the other products in the same category.
Analytical methods to identify and rectify the impact?
The impact of the post purchase biased reviews can be identified and rectified via regression analysis. This can be used for analysing the factors that the buyer might have used for buying the product. This will further help to determine which review can be considered and which can be ignored in a particular data set.

 

[SIDDHESHWAR JANGID]

Post-Purchase Rationalization

 

Many times we have purchased a product and then suddenly we realized this not what we wanted. Still we try to justify our purchase and give high Customer satisfaction feedback to save our back or to avoid cognitive dissonance. This Leads to Higher customer satisfaction score.

 

In Lean Six Sigma world, where Major KPI for the project is Customer satisfaction, Post purchase rationalization creates 

• Misleading positive satisfaction scores
• Reduced actionable insights because of disrupted data 
• Biased feedback.

To identify and rectify it's impact, the below methods can be used: - 

 

Sentimental analysis: - Generative AI can be utilized to check sentiments of customer feedback and identify this biasness.

 

Past data analysis: - By tracking customer satisfaction over time changes and patterns in the customer sentiments can be identified.

 

Customer behaviors: - Post purchase of product customer behavior can be identified like return rate, repeat purchase to look data skewness. 

 

Use lean six sigma tools: - Tools like Fishbone diagram, stakeholder analysis can be used to check the difference between actual and reported satisfaction scores.

[Priyanka Kotian]

Post Purchase Rationalization is often driven by customers impulsivity rather than necessity, hence in each 
case, the individual finds reason to justify their decision post purchase leading to misleading conclusions 
about how actually a customer is satisfied with the service or a product.

 

Let me share an example to explain - 

An XYZ client hires an interior design firm to decorate her home. She chooses to opt for all luxurious and 
trending options.
After the interior project is completed, the client notices some issues such as below:
1. Painting - The unique colors selected for painting the apartment doesn't quite match with her taste and seems
to be quite out of the place 
2. Hardware's - The choice of hardware selected for bathroom fitting are too lousy as per taste and doesn't 
coordinate with her other rooms 
3. Lighting - The designers choice is though stylish but too dim for evening time

Now despite of the all reasons above the XYZ client still choose to believe the investment done for interior 
designing is good justifying the below reasons - 
1. Focusing on positive aspect - The client focuses on how the room is made beautifully aligning with the 
trending design 
2. Ignoring the regret aspect - Client choose to believe that if she had gone for the cheaper option the result 
would be a disaster 
3. Status Justification - She rationalizes with the illusion of price that is higher the spend higher the quality 
that would impress any of her guests.

 

Impact on the Satisfaction Metrics - 
1. Overlooking practical problems - The client might not mention the discomfort of having dim lights during evening
time, resulting into skewed feedback that doesn't completely captures her experience
2. Inflated rating - She might rate the overall feedback very high focusing only on the 'wow' factor which again would result into skewed feedback 

 

Here are some methods to identify and rectify the impact - 

1. Behavior Analysis - 
Method- Tracking follow up with client with the request such as modifications or adjustment required in the current scenario
Purpose - Higher the rate of follow up would mean that the client was not completely satisfied in the first go

2. In depth Interview- 
Method - Conduct one on one engaging session with the client and ask open ended question 

Purpose - This qualitative approach allows deeper understanding and can uncover practical scenarios providing scope for development 

[Mayank Gupta]

Akkul has provided the best answer to this question. Well done!!