Revenue AI Tailored Promotion

Tailored Promotion

Tailored Promotions 

Many CPG companies spend up to 25% of their revenue on marketing and promotions even as retailers consistently ask for even more. Yet, most promotions fail to generate an increase in sales or to at least cover the costs of the promotion. Businesses cannot afford to gamble with guesswork odds. Salesforce indicates promotions have a strong influence on where 77% of consumers say they will shop, with 48% saying they speed up their purchasing decisions. There’s an enormous amount of data available to help businesses personalize their promotions while still respecting consumer privacy. The difficulty for most companies comes in making sense of all that data and being able to act upon when it is most valuable – in real-time.

Revenue-AI’s Tailored Promotions Module helps you manage four integral areas to promote the right offers to the right customer segments:

  1. Next-Gen Customer Understanding
  2. Upselling with AI
  3. Campaign Optimization with Promo Analytics
  4. Group Supply Optimization

A Next-Gen Customer Understanding. More interesting statistics from Salesforce are reflected with 65% of customers saying that personalized offers and exclusive discounts have a moderate to major impact on their loyalty. They also note that 50% of consumers are likely to switch brands if a company doesn’t anticipate their needs. To turn these points to your advantage requires walking a fine line between rich data and respecting personal privacy.  Revenue AI’s Digital Assistant, RAI synthesizes the vast pools of data of the data sets in your Data Catalog to get you up close and personal with customers. RAI answers your questions providing analysis on demand to determine the best channels to reach specific customer segments, see how they shop, what they buy, and to an extent, why.

Upselling with AI – Devise personalized coupons and promotions offline and online. Three out of four people who search for products on their smartphones visit a business within a day and lead to a purchase 36% of the time. What people do and are interested in buying online is reflected offline, with over 80% of sales still taking place in retail stores. RAI transforms the magic and good luck charms of traditional profitable promotions into a data-driven science. As RAI examines data sets including competitor pricing, consumer purchases metadata, and previous Occasion Brand Package Price Channel Architecture (OBPPC) strategies, users can better see what has and hasn’t been working. Equally important, RAI can provide “stop action” alerts on promotions that haven’t been successful. 

Campaign Optimization with Promo Analytics – RAI provides your team with cross-chain analytics with benchmarking and campaign planning advice based on top-performing categories and stores. Just as every store is different according to its local customers, we can’t expect every promotion to work the same. Augmented Self-Service Analytics capabilities provide your team with the ability to customize promotions on a per channel, cluster, and customer basis with both online and offline promotions. As RAI provides the ability to see promotion performance on a per retailer basis, your team also has the ability to make changes to them in real-time, too.

Group Supply Optimization – Help stores modify supply orders based on customer consumption patterns to avoid stockouts and spoilage. Each year in the United States alone, 43 billion pounds of food equating to about $52 billion dollars is thrown away by retailers. Stockouts occur most frequently when they’re likely to hurt most – during promotions. Stockouts aren’t just a matter of losing a sale; they factor into a loss in ‘size of the prize’. Customers will frequently choose a substitute, providing your competition to pull loyal customers away from you. 

Retailers are constantly improving their own predictive analytics and shelf replenishment practices. Even so, few retailers have the Level 3 RM capabilities required to manage SKU level inventories according to real-time purchases or market shifts on a per-store basis. Beyond RAI’s predictive analytics, alerts are generated to warn of impending stockouts and sudden fluctuations so you and your retail partners can respond faster.

The Importance of a Data Strategy

Most organizations are still just starting on their RM journey – basing decisions upon year on year comparisons or moving-day averages. Even organizations with mature RM programs relying upon traditional tools are left acting upon the analysis of last month’s data. Even an optimistic 50-50 split on effective promotions is indicative that companies, if not relying upon guesswork, are depending upon luck.

There’s always a drive to create better products, increase sales, and improve profit margins, and find better ways of connecting with customers.  This includes continuously improving our ability to make use of available data. More data enables more informed decisions. We see this in how companies like Amazon, Google, AirBnB, Uber, and others, dominate their markets. It owes in large part to their focus on data strategy. 

The Benefits of Augmented Self-Service Analytics 

As the amount of available data continues to grow, so does the challenge to make sense of it – to get actionable, data-driven insights that can be acted on before your competition. Traditional methods make that impossible and it’s a huge ask to expect everyone on your team to be a data scientist. Self-Service Analytics, according to Gartner, “Makes it easier and more cost-effective than ever before for non-specialists to perform effective analysis and better inform their decision making.” 

Revenue AI’s proposition allows organizations at any stage of their journey to leapfrog to the front of RM capability – easily and with surprising affordability. Our SSA and Augmented Analytics “data analysis on-demand” capabilities alone provides numerous benefits:

  • On-demand analysis providing detailed composites of customer segments – per retailer.
  • Know which channels can best reach the customer segments you are targeting.
  • Avoid promotions that will cannibalize purchases from loyal customers.
  • Stop Action alerts to safeguard against running unproductive promotions.
  • Immediate alerts of market shifts, imminent stockouts, and the ability to push promotions out in real-time, to reduce spoilage on perishable goods, for example.
  • Increased decision-efficiency increases competitive advantage by allowing actions to be taken when data is most valuable.
  • Democratization of data counters silos and increases team cross-functionality.