Type: Team project | Client: Procter & Gamble | Timeline: 2020-2021 (5-6 months) | Role: Product analyst
Improving Procter & Gamble’s consumer support process, while emphasising digitisation and seamless change management.
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How might we increase customer repurchasing and recommendations of products by a particular P&G brand, through improving brand trust?
Brief
As part of a university team project with 5 international students, we received a brief from Procter & Gamble (P&G). The objective was to develop a strategy of how the company might improve its consumer support process for one of its brands, through digitalisation and seamless change management.
To take on this challenge, P&G provided us with a case study and two datasets containing consumers’ feedback on the support process and their relationship with particular P&G products.
Role
In collaboration with two teammates from Romania and Lithuania, I was responsible for data exploration, qualitative and academic research, UX design, business analysis, and outlining the solution with regards to monetization and scaling opportunities. Similar to that of a product analyst.
Outcome
Two 12 minute presentations presented to senior executives at Procter & Gamble and other blue-chip firms such as Accenture, Vodafone, Ford Motor Company, and Fujitsu.
Deliverables included:
Data analysis (Neural network, sentiment, and correlation analysis) / PESTLE analysis / SWOT analysis / VMOST analysis / OKRs / Financial analysis / Change management plan / Risk log / Stakeholder interviews / Critical path analysis.
Visualised product strategy
Choosing Pampers
We identified a strong positive correlation between P&G consumers’ trust in a brand and their frequency of repurchases and recommendations through our data analysis models. This was further supplemented with academic research on brand loyalty which supported our findings. Pampers were one of the few brands provided in the dataset by P&G that contained sufficient data for our analysis to be statistically significant, and the discovered issues were tangible enough to meet the project requirements; thus this led us to focus our efforts on this brand specifically.
Our sentiment analysis and text mining identified that most issues were concerned with P&G UK’s discontinued Pampers Club Application. The latter was a loyalty scheme allowing customers to collect points with purchases and exchange them for rewards.
The identified problems with the Pampers Club Application were both related to technical issues and a frustrating user experience, which undermined consumers’ trust in Pampers. This is a core issue because of the correlation between brand trust and consumers’ likelihood of repurchasing and recommending a P&G brand’s products.
Mapping techniques such as UML diagrams, wireframes, and medium-fidelity mockups were used to conceptualise our strategy
Our proposal
Reengineering and improving the existing Pampers Club App, focusing on exceeding customers’ expectations, establishing trust, and increasing engagement with the brand. Our proposal did this by improving the already existing reward scheme in the application through gamification and user progression by matching customers’ expectations of prizes with their purchases. And developing a brand community for peer-to-peer Q&As and discussions, thus improving response time, engagement, and brand ownership.
Detailed considerations
01 Making the platform invite-only, thus limiting bargain-hunters, increasing brand ownership, and facilitating change and user management
02 Incorporating a voting dynamic to the brand community, thus ensuring Pampers staff and power-users can prioritise top-voted posts
03 In-app marketing and user research features for Pampers
04 Data-enabled learning through collected user data, enabling P&G/Pampers to utilise targeted marketing and enhance product development
Change management
We believe the changes and distribution of the required resources resulting from our proposal would happen seamlessly within Pampers’ current environment.
This is because of 3 core reasons:
01
P&G UK already has experience with launching and operating the previous Pampers Club App and its reward scheme
02
P&G UK runs brand communities from beforehand, such as SuperSavvyMe
03
Pampers in the US already have incorporated unique QR codes on their packaging as part of the reward system for the Pampers Club App, which is still running in the US
The analytics tool Tableau was used for data exploration and analysis
Financial analysis
We forecasted our application would need a one-time investment of 370,000 pounds for app development, marketing, changes in product packaging, human resources and employee training. Annual costs are estimated to be around 16,000 pounds. Running the reward scheme could cost around 5.4 million pounds per year.
Still, research by Capgemini highlights that a dynamic similar to our brand community may increase annual revenue up to 5% as emotionally engaged customers spend twice as much. This is further supported by research outlined by Harvard University, emphasising that acquiring new customers could be up to 5-25 more expensive than retaining one. Moreover, an increase in retention may increase profits by 25-95%, however, being critical and assuming the application may underperform we only considered a 10% increase in operating profits.
Calculating the profitability of our project using a Net Present Value model, we underlined that the return on investment would be 9.15 million pounds by 2025.
What I learned
This project provided me with a wide array of experiences and tuning of skillets related to data-driven analysis and product strategy:
It was a great learning opportunity to combine qualitative research with advanced data analytics to understand customer needs, identify business/financial opportunities, and perform feature audits.
It provided me with a nuanced perspective on change management and adopting a holistic view on organisational processes, stakeholders, and information technology to ensure a feature/product launch is successful in all areas.
It allowed me to understand better how data-enabled learning could be utilised for continuous product improvement and as an asset for revenue gains.