Shopper Intelligence System

Consumer Packaged Goods (CPG) companies collect and use consumer, shopper and user intelligence to better understand consumer behaviors, preferences, and trends. This data-driven approach helps them improve their products, marketing strategies, and overall customer experience.

More specifically, shopper intelligence, the intent and behavioral choices a ‘the point of purchase’ are a crucial as a significant part of purchases are decided in-store. This may be less relevant for repeat purchases (e.g. your weekly groceries), but very relevant for infrequent, high-value, high-involvement consumer goods categories like electronics, cosmetics, skin-care, etc, especially if it involves some degree of guidance form the store personnel.

Traditional ways to capture shopper intelligence are challenged and more effective ways are needed.

Luckily MOOS can help

Shopper intel as CPG lifeline

Shopper intelligence can be used for:

1. Sensing trends: identifying emerging trends and shifts in shopper behavior to adapt strategies and capitalize on new opportunities. This can include comparing shopper intelligence with competitors to identify strengths and weaknesses, relative performance, and develop competitive strategies.
2. Shopper segmentation: segmenting shopper based on behavior and preferences to target and approach them differently
3. Product development or range extension(s): using shopper intelligence to inform product development
4. Pricing & promotion strategies: analyzing purchasing patterns to optimize pricing models and implement dynamic pricing, promotional offers, and competitive pricing strategies.
5. Personalized marketing: crafting tailored campaigns to increase engagement, conversion rates, and customer loyalty.
6. Operation & distribution management: using sales data to manage stock levels and supply chain operations. Reduce overstock and stockouts, improve supply chain efficiency.
7. Improving the overall shopper experience, e.g. improving presentation, layouts, customer service, and providing novel interfaces or interactions

In short, capturing solid shopper intelligence is the lifeline of CPGs. Retailers and third parties realize this and go to great lengths to only selectively share these insights and monetize these with subscription feeds. Retailers also make sure that the access to really capture meaningful, timely, accurate and actional shopper intel in their shops is guarded carefully.

The traditional way & their limitations

Here’s how they typically collect and utilize shopper intelligence:

1. Point of Sale (PoS): data collected at the point of purchase, including transaction details is a great source. Typically use to analyze purchasing patterns, identify popular products, and track sales performance. Sadly, this source is only provided in delayed, aggregated ways to suppliers, either directly or through 3^rd parties, making this difficult to use for quick feedback and iterations.
2. Loyalty Programs: systems that reward customers for repeat purchases. Think of a loyalty card with a point collection system. Again, a great source of intel for detailed shopper preferences and purchasing habits over time, but tightly guarded by the retailers.
3. In-Store Analytics: using technologies like heat maps, video analytics, and RFID tracking within physical stores to monitor foot fall, dwell time or patterns, optimize store layout, and understand in-store behavior. Like the previous sources, these require access to the shopfloor and are restricted.
4. Surveys and Feedback: directly asking shoppers for their opinions through (online) surveys, feedback forms, and focus groups. This can help uncover shopper satisfaction, preferences, and areas for improvement, but relies on direct or 3^rd parties for data collection, is relatively costly and slow.
5. Social listening, e-commerce and mobile analytics. This is rich source to understand perceptions, identify trending topics, gauge customer sentiment, analyze online shopping behavior and segments. It also has the ability to test & learn, with AB testing of variants. This is a great source of shopper intel, reserved for the CPG that have their own site(s) and DTC operations. Naturally, that doesn’t apply for every CPG player, limited to its coverage in terms of product/regions and does not necessarily translate to a real-world shopping setting.
6. Third-Party data: insights from market research firms and data aggregators to compare against (industry/peer) benchmarks, enrich internal data, and gain a broader market perspective. These services have become a necessary evil for CPG, not because of the great detail and insight, but because of the lack of any alternative.

In short, CPGs need to resort to mix of methods to collective get a reasonable grasp of shopper intentions and preferences. There’s a great divide between selected CPG players that either have own retail operations, close retail relationships or sufficient clout to demand a degree of shopper intel sharing – and CPG players that do not have this luxury or not across the board in all geographies.

For these, MOOS can provide a way that to circumvent the retail constraint or add to the mix of shopper intelligence gathering if there is a basis for retail collaboration.

MOOS powered shelves for smart shopper intelligence

They key towards collecting meaningful shopper intelligence is the ability to test & learn, iterate quickly and thereby create feedback on different aspects. Basically, this is the concept of AB-testing that is perfected online, but then applied to a real-life setting with product placements in retail outlets.

The MOOS system can connect shelves in non-intrusive, invisible way and pick-up pretty much any transaction of shoppers with the products. So, product pick-up, place-back actions and all derivates, like rotation over time or across different products, shelves, locations. When you mix in other variables of the offering, e.g. price or discount, placement on the shelf, secondary placement, in-store comms, etc. you can easily enrich the shopper data capturing to capture intent across the full marketing mix.

We distinguish two approaches to deploy a smart shopper intelligence system, which can be used in combination as well:

1. Sample across shelves. Create a representative sample of shelves across products, outlets or shopper segments, to deploy sensors and collect intelligence. This could rotate or have a temporary nature, e.g. accompanying a promo or introduction event. Both the sampling and temporary nature can help the agreements between CPG players and retailers to deploy this intelligence collection on their turf, especially if insights and benefits can be shared.
2. Connected assets, like displays, coolers or in-store merchandise material. While approval from the retailer is still needed, it might be easier if the CPG sponsors the collateral that is deployed to the trade. Instead of a traditional, analog version, a connected version with the MOOS system can be deployed.

Retailers might actually be far more collaborative and easier to convince. In fact, the MOOS system has great operational benefits for shop operations, creating the feed for shelf actions (count, check, replenish, clean, etc), that help drive higher shelf availability and lower operating costs. This benefit alone, may already be the prime reason for retailers to connect their shelves.

In fact, some retailers not only see this as their ability to boost operational efficiency or avoid stock-outs, but also as an extension to vendor monetization opportunities. We see an increase in the richness of the data-services that retailers provide as an extension to providing their PoS data as a service.

How to get started?

Some situation are better suited than others to create a shopper intelligence system. At MOOS, we have a quick diagnostic approach to help you asses the suitability to create sample shelves or connected assets with the MOOS system.

Just get in touch and we can help you explore the possibilities.