Data-driven Approach on Sales Strategy and Execution

Running and sustaining a business is not based on pure instinct, especially when you want to grow a business empire. A company used to be more personalised with face to face interactions. A sales representative can engage with prospective clients, and using instinct, determine if they are an ideal customer.

However, due to changing human behaviour, advancements in technology and the pandemic’s hurdle, the world has shifted to a virtual platform where personal interaction is limited to non-existent. Companies face the challenge of building trust and are now executing a buyer-first approach after they have understood the customer’s needs.

Analytics is a crucial part of your company’s roadmap. Useful analytics establishes metrics for planning and executing actionable results, giving you an understanding of your company’s past performance and future predictions. Using a data-driven approach, your company can form a personalised and targeted plan to satisfy your customer. A company’s growth relies on the level of analytic maturity used.

 

Analytics Maturity Model

Analytic maturity is the first analytical model introduced in the middle of the 2000s by Wayne Erickson. It is a design used to assess an organisation’s effectiveness to execute data analysis and decision. The original design is segmented into five stages. However, each company can personalise their own model depending on its purpose.

 Descriptive analytics:  What happened?

This is the primary stage where pieces of information are collected and interpreted, developing a conclusion. This is the level where you recognise your company’s present and past circumstances and analyse historical data referring to changes that happened and their extent unto the present and comparing the two.

Relevant data to collect are ad clicks, website traffic, conversion and revenue. Doing this weekly can give marketers a clear interpretation of what is happening in the company. They must remain consistent, in cases that there is a dip in revenue; a diagnostic analysis must be performed.

Return on invested capital (ROIC) is a type of descriptive-analytic metrics to analyse net income, total wealth, and dividends. These are used to compare your company with your rivals.

 Diagnostic analytics: Why did it happen?

 This provides a more in-depth analysis identifying the root cause of the problem. For example, your revenue is down 10% from last quarter’s study; using diagnostic analytics will give you a clear view of the reason behind this deficit. Is this coming from extra ad spend, increase in the abandoned cart or SEO based on changes in Google’s algorithm affecting website traffic? Basically, the stages involved in diagnostic analysis are identifying the problem, having an overview of what you think happened, filtering your diagnosis and providing supporting evidence leading to a fact-based conclusion.

 Predictive analytics: What will happen?

 This is the level where data is used to predict the future. Here is when you weigh the results if you decide to change an aspect of your business. What will happen if I use chatbots in customer service?  

Using buying trends and patterns will enable you to establish a system to adapt and predict sales outcomes. For example, predictive analysis will help companies identify which customers will likely avail of promos, which you can capitalise on by sending them a voucher.

 Prescriptive analytics: What should I do?

Considered the transformative stage, here is when your company uses data to propose the best actionable plan and predict potential outcomes. Here is when you take action. This concept exploits how a business can grow faster, optimising sales operations and effectively dealing with risks.

In marketing and sales, prescriptive analytics helps identify the best marketing approach, like bundles paired with the best price.

 Modern Big Data Analytics

 Cognitive analytics: What don’t I know?

Likewise known as intelligent analytics, a data-first approach is entirely based on all relevant information. This allows companies to have a deep understanding by using extensive research for brand positioning and establish a customer-centric approach. This is possible with the use of AI and data analytics.

 The amount of data captured in 2020 was 59 zettabytes. These data came from all around the globe from social media posts, mobile phones and others. Such big data is impossible for humans to study manually, thereby creating a need for different software systems.

Cognitive analytics is the next big thing that utilises artificial intelligence high computing capability in data analysis—the smarter and more effective way for businesses to gather real-time information for immediate action.

Business growth highly depends on the agility and quick decisions of a company. Companies that utilise big data analytics have gained a competitive advantage over a small business. It helps with a company’s consistent and quality service and improves personalised services and marketing insights.

Let’s use Netflix as an example of how cognitive analytics helps a company increase marketing insights and deliver tailored services.

Netflix has over 100 million subscribers all over the world. Have you ever wondered how Netflix shows you suggestions on the next film or series to watch? Netflix uses big data analytics to evaluate your past search and gain insight into your interest and behavioural patterns. They focus mainly on your behaviour to tailor the best customer experience for you.

Impact of Data-driven Approach

 Dynamic Revenue Plan

Having a data-driven approach will help you improve your company’s growth using facts in analysing patterns to develop an agile revenue strategy, giving you a solid reason to allocate funds for optimal sales and profit. Lord Kelvin said, “If you cannot measure it, you cannot improve it.”

 Targeted accounts

 Using a data-driven approach decreases customer acquisition cost, as your company prioritises ideal clients and disposes of non-buying customers.

 More accurate forecast

 Data-driven analytics provides accurate forecasts and decisions regarding market changes, customer preferences and rival companies.

 Increased productivity

Data can help your representatives use their time wisely by effectively targeting potential customers.

 

Take Away

Every company needs to use a data-driven approach for guidance to survive and grow the ever-evolving market trends. Relying on fact-based data is the only way to assess, forecast, strategise and execute strategies objectively without hesitation.

 

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