Why A CPG Firm’s Business Intelligence Needs AI

INFORMATION IS THE OIL OF THE 21ST CENTURY, AND ANALYTICS IS THE COMBUSTION ENGINE – GARTNER

This statement rings particularly true for CPG businesses that are typically spread across multiple locations – countries, states, cities, counties and so on. Added to this, CPG enterprises are defined by the inherent diversity and complexity in the 5 Ps of marketing – product, price, promotion, place and people.

Data analytics experts are now working hard to translate the massive amount of data being generated to simplify and create an optimal mix of the 5Ps. Every element of the 5Ps is being redefined with an intelligent combination of data and strategic thinking.

Success in CPG businesses rests primarily on two factors: accuracy and speed, both of which are enabled by artificial intelligence in CPG business intelligence.

This spans across a variety of activities:

Planning marketing campaigns
Trade and Consumer Promotion
Supply chain management or
Assortment optimization

Highly accurate information is critical at various touchpoints in order for companies to leverage analytics in order to become key competitors in their niche.

There are various advancements that have been made in AI-related fields – Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics and others, which have radically altered how Business Intelligence works. When AI is integrated with these advancements, there is massive potential for the applications of data analytics in CPG businesses.

As a worldwide trend, CPG companies are increasingly starting to realize the value of BI and analytics and the tremendous advantages they offer.

Let’s take a look at the specific shifts in the industry which are enabling BI and analytics to quickly become an integral part of doing business today:

Internet proliferation: As customers become increasingly well-informed, their expectations have increased well beyond the traditional brick and mortar ordering platform.

Global expansion: As international trade becomes easier, opening up access to various new avenues to source products, CPG organizations have to now work with diminishing borders and learn to deal with the subsequent changes to the organization’s supply chain.

Data-Driven Revenue Growth: An interesting development recently has been the institution of mutually beneficial relationships between retailers and CPG companies, where they are able to exchange data and consumer insights to improve processes and outcomes for both parties.

Supply Chain Optimization: As market demands increase rapidly, CPG companies have to work hard to optimize the supply chain for greater efficiency and speed and simultaneously do away with conventional methods that don’t produce results.

Innovative packaging and marketing: More and more customers are now turning to online shopping. With this rapid shifts in buying behaviors, companies must look into how they’re presenting themselves to their customers, in terms of packaging and marketing.

Ironically, what is lacking in traditional BI systems is the “intelligence” part. This has resulted in these systems not being user-friendly and also not generating the kind of deep insights that CPG companies can leverage to drive real business outcomes.

Why CPG BI Needs AI

AI Leverages Unstructured Data

Finding meaningful insights is akin to looking for a needle in a haystack. CPG businesses gather massive amounts of data from various sources, primarily important customer touchpoints such as social media, events, POS, all of which are highly crucial in devising an analytics-driven strategy. However, most of this data is in unstructured form. AI technologies such as Machine Learning (ML) harnesses this raw, unstructured into data that generate meaningful insights into improving business results.

AI Makes Data Work

With Artificial Intelligence, decision makers can focus more on gleaning insights from raw data, rather than expend time in analyzing it. Allowing and leverage AI to do all the hard work for you by analyzing each bit of data and then generating rich insights that your business can immediately use, saves time and dramatically impacts the bottom line.

AI-Powered analytics such as predictive and prescriptive analytics not only process large amounts of data but also provide fact-based recommendations and tailored insights for decision-makers.

AI Adds Predictive Intelligence

Too often CPG businesses are too focused on what they would like to sell rather than trying to know where a customer stands in their business journey.

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Predictive Intelligence will allow CPG companies to overcome this challenge by delivering customized experiences unique to each consumer. It enables the marketing department to observe customer behavior, and closely monitor each action taken, to build an in-depth profile of consumer preferences. This information is then leveraged to deliver highly relatable and specific experiences to each consumer in real time – across various channels. Using AI, businesses can hone down on exactly what their consumers need and want. One of the most critical applications of AI in adding this layer of predictive intelligence is not just the ability to provide tailored recommendations, but also the ability to accurately forecast in crucial What-if scenarios.

Predictive analytics also help in forecasting sales and marketing promotions. It predicts and recommends what promotions/campaigns to run when and where for a high-yield ROI.

AI Drives BI Adoption

AI-powered chatbots allow convenient and faster data accession from the existing Business Intelligence software or analytics tool. When deployed into organizational messaging platforms like Skype for Business, Skype, Telegram, Slack etc., these bots extract relevant insights from the tool/software and provide them to the user via chat.

Chatbots have a plethora of applications for the adoption of BI:

Chatbots enable you to find important data at your fingertips. Instead of having to log into the BI software every time, users can have a chat with the bot and obtain insights, right within the messaging app.
Field sales teams need quick insights which can provide by chatbots. Chatbots offer you data on the go. Since chatbots are deployable on most of the messenger apps, users can get BI analytics/data while using the already highly-used messenger app.
The answers provided by AI chatbots are not limited to only text format. Powered by Natural Language Processing (NLP) and Machine Learning, these bots can understand users’ intent and send the data in the necessary format – text, simple graphs, pie charts, heat maps etc.
Chatbots can initiate conversations and push personalized notifications, updates, alerts, anomalies in trends etc. directly to employees.
Group bots act as helpful team members and can send required analytics from the BI if there is a need for an ongoing group chat.
Chatbots act as helpful assistants to such users. Bots essentially eliminate the need to visit various BI tools or go through complicated navigation flows. They also empower employees in making data-backed decisions in a hassle-free manner.
Chatbots eliminate workforce dependency on the IT department. Any employee can obtain required insights instantly from the BI system.
Sales personnel performance is typically indicated by several metrics like OTIF (On time in full), MSL (Must stock list) and various others. Allowing this data to become easily accessible to sales teams from their mobile devices, and via a single interface, will ensure that they are getting enough time to focus on lead nurturing. An additional benefit would be if they are able to transact with the LOB systems based on this information, using the same interface.
Chatbots enable better sales and marketing investments and promotions.

Supply Chain And Inventory Management

Supply chain structures and operations for CPG businesses are usually complex i.e they have to ensure the right amount of products are available to consumers based on marketing and sales promotions, product demand, and various other factors.

The aim of any effective supply chain structure is that goods should be delivered at minimal transportation and operational costs. With data, they can accurately figure out how many products should be in the inventory, how many trucks will be needed, what is the OTIF loss estimation etc. The entire operations become insight-driven with the usage of AI.

Whether it is identifying cost reduction opportunities, performing demand analysis, or resolving high-impact issues, AI helps CPG companies ensure that the supply chain is running without glitches.

By identifying exact causes of leakage, OTIF losses can be greatly reduced. This also means you can expect to see increased operational efficiencies and reduced operational costs. Getting product assortment right is highly critical to CPG success. While in other areas such as inventory management and pricing, there is still plenty of data available, product assortment can be a little more complicated to maneuver and get right. Leveraging AI will help you overcome this deficiency and gain insights into various factors that will enable you to optimize product assortment and subsequently generate higher profits.

Better Revenue Management Strategies

For CPG enterprises, key decision-making is centered around strategic pricing, marketing campaigns, sales trade promotions, assortment optimization and inventory management, thereby making Revenue Growth Management (RGM) a very important factor to consider.

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Given the competitive and fast-moving nature of the current business environment, it is imperative that RGM executives are spending less time deciphering analyzed data and instead of spending more time obtaining and implementing actionable insights from the analysis. However, most traditional analytics tools do not support such sophisticated mechanism, forcing users to review multiple reports to arrive at insightful conclusions.

AI-powered advanced analytics like predictive and prescriptive analytics implement a fact-based approach. These technologies operate by identifying trends, patterns, and anomalies in the feeded data. Thus, they are able to deliver relevant and actionable recommendations and insights to users. This fosters an environment that is conducive to convenient and faster decision-making. They help Revenue Management executives make high yield pricing and promotion strategies and recommendations for sales and marketing.

Conclusion

As CPG data increases without bounds every passing day, companies have to relentlessly look into how they can unlock the value of this data, in order to remain competitive in a cut-throat environment. CPG companies will have to look beyond the usage of conventional analytics tools, generating a bare minimum of insights, most of which are actually generic and non-actionable. Now more than ever, it is critical that CPG businesses are turning their attention to technologies that can both provide them with meaningful intelligence, and be easily incorporated into daily workflows.

AI is the ideal dynamic add-on to existing BI platforms to convert already available data into rich and meaningful intelligence that will eventually produce powerful business outcomes.

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