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AI in Marketing and Sales Decisions

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The Point: The world is becoming more volatile, uncertain, complex, and ambiguous than ever before, which makes predicting customer behavior and adapting to changing market conditions more challenging. However, some companies have successfully leveraged AI models to predict outcomes and adjust their marketing and sales efforts, giving them a competitive edge. By analyzing historical consumer behavior data, these firms can predict the likelihood of customers responding positively to marketing campaigns, detect potential churn, and redirect sales efforts when predictions go off track. In effect, they run a large number of digital experiments that help them respond to market changes more quickly than their competitors. In this article, we explore how firms can use AI models to predict customer behavior and adjust their marketing and sales accordingly. We present two case studies that demonstrate how AI models helped a global trading firm and a real estate property developer to adapt to changing market conditions and achieve better business outcomes…Enjoy!

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Why AI Is Changing How We Make Marketing and Sales Decisions

In the analog world, it was challenging to establish a causal link between marketing investments and customer response. However, the digital world has made it easier to build causal links by running a large number of relatively cheap experiments. Firms have the ability to track customer responses at every stage of their journey. These stages include search, click, purchase, and even consumption. This process leads to an exponential increase in the amount of data available to firms. The data provides valuable insights into the customer journey. The insights can be used to improve customer experience and inform business decisions. This data tracking is made possible by technology and data analytics.

Some firms excel in adapting their use of customer data to respond to changing marketing conditions. These firms are faster than others. They can quickly pivot in response to uncertain conditions. These fast-acting firms use AI models to predict outcomes at various stages of the customer journey. For example, they analyze historical consumer behavior data and predict the likelihood of a customer responding favorably to a marketing campaign. This proactive approach to managing customer relationships enables firms to predict which customers are likely to churn and what corrective action can be taken to prevent the customer from defecting. Meanwhile, their competitors react after the customers have already left.

Firms rely on AI feedback to adjust marketing and sales when predictions fail due to external factors. They run digital experiments to respond quickly to market changes and gain a competitive edge. AI tools, while not perfect, can transform decision-making in marketing and sales.

Case Study: A Global Trading Firm

In early 2019, a trading company employed AI-based prediction models to monitor the RFP-based purchasing processes of its clients. The firm focused on quality as the primary criterion for being short-listed, which allowed it to pursue select opportunities.

However, the AI-model predictions made by the firm began to prove incorrect by May 2020. Upon further analysis, it was discovered that delivery-related terms were better indicators of being short-listed by clients. As a result, the company quickly and effectively altered its engagement model globally. Thanks to AI, firm leaders could now anticipate intermediate outcomes in clients’ purchasing processes and quickly adapt the marketing and sales approach to match shifts in the market, rather than relying solely on macroeconomic data or revenue shortfalls after a couple of quarters.

With the help of AI, the trading company was able to adjust to market changes and achieve better results. It promptly changed its global engagement model, aligning sales and marketing strategies with market shifts.

Case Study: A Major Real Estate Property Developer in the UK

In January 2020, a UK real estate developer conducted a study on tenant incentives. The study aimed to find the best way to incentivize tenants in corporate spaces. Their discovery showed that offering a rent-free period for the first few months of the lease was the most effective incentive. The study factored in the low probability of corporate spaces remaining unrented. The findings suggested that offering a rent-free period would attract more tenants, leading to higher occupancy rates. The developer concluded that providing a rent-free period would be the most attractive offer to potential tenants.

The developer and marketing team cooperated for the incentive. Targeted campaigns emphasized the rent-free period’s benefits for business expansion. Increased occupancy and profitability were achieved, establishing the developer as a market leader. Understanding ideal incentives and data-driven insights are crucial in competitive industries like real estate.

The case study emphasizes the significance of comprehending and examining the ideal incentives to draw and retain clients. This is particularly important in fiercely competitive industries such as real estate. Through the use of data-driven insights and collaboration with their marketing team, the developer established an efficient incentive program. The program proved successful, driving business growth and achievement.

SUMMARY

In conclusion, the case studies of a global trading firm and a major real estate property developer in the UK demonstrate how AI models can help firms adapt to changing market conditions and achieve better results. Overall, AI models in marketing and sales give firms an edge in a volatile market. It’s uncertain and complex, and the environment is ambiguous. By leveraging data-driven insights and working with their marketing teams, firms can create effective incentive programs that ultimately drive business success.

Sam Palazzolo, Managing Director

What can Generative AI do for Sales and Marketing? 5 Tips!

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The Point: I just participated in a roundtable discussion titled, “Generative AI: Friend or Foe. At Tip of the Spear Ventures, we recognize Generative AI as a technology with potential to transform Sales and Marketing. So in this post, we’ll explore 5 Tips on What Generative AI can do for Sales and Marketing… Enjoy!

Transform Your Business.

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5 Ways Generative AI can Impact Sales and Marketing

Here are 5 ways we view Generative AI impacting Sales and Marketing processes in the future:

#5 | Personalized Content Creation

Generative AI can help Sales and Marketing teams create personalized content at scale. By analyzing data about individual customers, Generative AI can create tailored content, such as emails, blog posts, and product descriptions, that are more likely to resonate with customers and drive engagement.

#4 | Lead Scoring and Qualification

Generative AI can help sales teams prioritize leads by analyzing data about customer behavior, such as website visits, email opens, and social media activity. By identifying the most promising leads, Sales Teams can focus their efforts on the customers who are most likely to convert.

#3 | Sales Forecasting

Generative AI can analyze historical data and current market trends to provide accurate Sales Forecasts. This can help Sales Teams plan their activities more effectively, such as by identifying the best times to launch new products or run promotions.

#2 | Chatbots and Customer Service

Generative AI-powered chatbots can be used to provide personalized Customer Service at scale. By analyzing customer inquiries and providing relevant information, chatbots can improve the customer experience (CX) and reduce the workload of customer service teams.

#1 | Predictive Analytics

Generative AI can help Marketing Teams make data-driven decisions by analyzing customer behavior and predicting future trends. By identifying patterns in customer data, Generative AI can help Marketers optimize their campaigns, identify new target audiences, and improve their overall marketing strategy.

SUMMARY

Overall, Generative AI has the potential to significantly improve Sales and Marketing processes by providing Personalized Content, Prioritizing Leads, Forecasting Sales, improving Customer Service (CX), and providing Predictive Analytics.

PS – The actual prompt I could have entered in ChatGPT would have been, “What are 5 ways Generative AI will impact Sales (and Marketing) Processes moving forward?” 😉

Sam Palazzolo, Managing Director

How Brands Use Pricing Strategy to Improve Customer Experience and Increase Brand Value

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The Point: Is the pricing strategy you establish for your organization’s products/services the “right” price? By the “right” price, what’s really at stake is what will enhance the customer experience and increase your brand value. From the pricing studies that we’ve conducted, we’ve seen a number of organizations that are challenged while at a 3-pronged fork in the road when it comes to establishing pricing strategies. In this article, we’ll explore an overview to pricing strategy and the inherent benefits associated with customer experience and brand value… Enjoy!

Pricing Strategy 101

Pricing Strategy can be a powerful tool to increase brand value and attract new customers. Brands use value-based pricing to create a range of products and services at different price points. The goal is to make each product or service stand out from the rest of the market. To do so, brands must create a meaningful difference between their products and those of competitors, and give consumers an apparent reason to pay more. Brands that employ a premium pricing strategy often target a particular segment of consumers.

Pricing Strategy as Competitive Advantage

While low prices are often appealing to consumers, they are also perceived as cheap and can erode brand value. Price changes must be carefully considered, as they are almost impossible to reverse. If a competitor is already offering a product or service at a low price, they may have the upper hand. Using discount pricing can help a business to attract more foot traffic and to clear out old inventory, but it could also lead to negative effects on the perception of quality.

Pricing Strategy and Organizational Goals

Developing the right pricing strategy is essential for any business. There are many factors to consider, so it is a good idea to calculate COGS, profit goals, and customer needs to create the optimal pricing strategy for your product or service. Once you’ve done that, you’ll be ready to start your pricing journey.

Pricing Strategy – First Steps

The first step in creating a profitable pricing strategy is to define your target audience. A target audience’s price sensitivity will help you determine the appropriate pricing strategy. For example, if you have a product with high price-sensitivity, price-skimming may be a good strategy. If you have a limited market, a low price strategy may work well for you.

Pricing Strategy is an ongoing process. Ideally, you should use CRM software to segment your customer base and test different pricing strategies. Developing a successful pricing strategy requires time and effort. However, the right pricing strategy should be well-supported with your go-to-market strategy and marketing plan. In order to determine the best pricing strategy, it’s important to gather feedback from your sales team. You should also evaluate your competitors and gauge their pricing strategy.

There are many different ways to price your products and services. For instance, you can price a product or service above your competitors, while you might be able to match them using a value-based model. For a more profitable strategy, you might want to price your products or services below your competitors. This strategy, however, requires more research and insight into your competitors. It’s also important to evaluate your own costs and resources in order to determine which pricing strategy works best for your business.

Another pricing strategy is loss-leader pricing, where you offer a low-priced item with the hope that consumers will buy more. This strategy works well if you want to attract new customers. If the price of your product or service is a significant part of your business, you might choose to charge higher prices for ink to attract more potential customers.

SUMMARY

In this article, we’ve explored pricing strategy from an overview perspective along with inherent benefits associated with customer experience and brand value. Crucial in establishing the pricing strategy are identification of competitive advantage and organizational goals. We’ve also explored a few additional “first steps” that should be considered in doing so.

Sam Palazzolo

KEYWORDS: Pricing Strategy, Competitive Advantage, Customer Experience, Marketing, Competitive Strategy, and Organizational Goals