Considering that closing sales – enough to be profitable – is the main way organizations fund themselves, the importance of making savvy decisions that drive sales is evident. Artificial intelligence (AI) has become a valuable tool to help leaders make confident decisions faster. AI is regarded as a must-have item in the budget of many companies.
- In a survey by Gartner, 80% of business leaders stated that AI had improved their decision-making accuracy.
- A study by Accenture found that AI-enabled chatbots have a 90% accuracy rate in answering customer queries.
- According to a study by PwC, AI has the potential to improve data accuracy by up to 80%.
Source: (1)
While AI excels at rapidly reviewing input to produce high-quality data, not all results are advantageous for decision-making. AI-generated data can be detrimental if accuracy, timeliness, intent, and the right questions aren’t asked. This article explores five effective strategies for using AI to make evidence-based decisions.
1- VERIFY THE ACCURACY AND TIMELINESS OF THE DATA
Data collected by AI is only as good as it is accurate, which enormously impacts the quality of the data produced by AI tools. The technology can process and sort through an astounding amount of digital information. While this ability is one of AI’s benefits, it can become a drawback if the information collected is skewed, inaccurate, or simply wrong. So, how do you differentiate good data from incorrect, insufficient, or blatantly bad data?
First, study the source(s) from which the tool pulled the information. There are infinite places where AI sources data, but you can pinpoint the right one according to the tool. You might ask: What is the source of the information we are using for this specific endeavor? It could be anything from how sales leads interact with your website to social media monitoring.
For example, if your objective is to study how potential customers interact with your website, you must determine where to pull the information and whether it is correct. Google Analytics is one option, however, it calculates sessions, users, and bounce rates, which may differ from other website traffic tools. You might opt to use Crazy Egg instead since it has more robust features for behavior and traffic analytics and tends to be a more reliable source of information. AI’s data output will only be correct if the source’s input is accurate.
Timeliness is another critical factor. Competitive intelligence or market research conducted two years ago is significantly less reliable than the same research conducted two months ago. Make sure the following sources are up to date for the timeliest AI-produced data:
- Social media monitoring
- Market research
- Market Intelligence
- Customer interaction data
- Customer relationship management (CRM) data
- Customer surveys and feedback
Keeping your CRM updated is imperative to executing successful AI-driven sales efforts. Your CRM is the key to the kingdom; the more updated and accurate it is, the higher quality data you will get from AI tools.
2- BE METICULOUS WHEN ENTERING INFORMATION
Accuracy is just as important when manually entering information used by AI. Remember, the golden rule of AI is that you get out of it what you put into it. AI technology has many strengths and is becoming more advanced by the day, but for now, it relies entirely on the information fed to it.
Conduct regular audits of your website, email campaigns, social media accounts, online sales materials, online customer support portal, and the all-important CRM. Pull employees from different teams or departments into the effort to ensure that no detail gets overlooked. Consider including service/support, finance, IT, marketing, production, and shipping departments as part of those efforts.
Additionally, take any feedback you get from sales leads about their experience with your public-facing digital properties seriously. Do not hesitate to resolve the issues they bring up, as doing so could prevent the company from losing future sales.
3- IDENTIFY THE INTENT OF THE TASK
What is the end goal for the AI sales tool in question? It might be:
- Collecting contact information from potential sales leads.
- Driving potential customers through the marketing funnel.
- Identifying which sales leads are most likely to convert.
- Learning more about your target audience.
- Learning more about your competitors and how you stack up against them.
- Creating brand awareness for your target audience.
- Establishing leadership at your organization as trustworthy, knowledgeable thought leaders.
The intent is critical because if the AI tool is not acting with the right intent, chances are good that it could generate inaccurate information for the end goal.
4- QUESTION WHETHER THE RECOMMENDATION HAS A SOLID EXPLANATION
AI can make recommendations based on the data it produces. It might be tempting to act on these recommendations, assuming that solid reasoning is backing them up. But making this assumption is a potentially costly mistake.
Reaching smart sales decisions requires thoughtful reasoning, which is something that AI lacks. Carefully evaluate AI recommendations to verify that each one has a solid explanation. If the logic is lacking or does not make sense, you might need to adjust the data input or other sources the AI tool uses. You can also consider an in-person strategic meeting designed to hear feedback from crucial department leaders. AI data-driven recommendations combined with a participatory group meeting can be a powerful combination when decision-making.
5- WEIGH THE RISKS AGAINST THE BENEFITS
AI is not immune to making mistakes – just like any other form of technology. Leadership should thoughtfully weigh the risks against the benefits when deciding whether to implement any sales-related AI tool. Ask questions such as:
- What are the potential consequences of this tool failing its task?
- What is the severity of the possible adverse effects? Mild? Moderate? Catastrophic?
- Could we get more accurate results with a different tool, or if we did the work manually?
- How much time will the tool-free up for sales employees versus the time spent using it?
This is a sampling of a long list of risk-versus-reward questions leadership should pose when deciding on AI tools for sales-driven efforts. The decision is a major one, as it impacts the chances of your sales team achieving success. It can also affect how your target audience views your organization.
INFORMED DECISIONS LEAD TO BETTER SALES OUTCOMES
Leveraging AI tools to make sales-driven decisions is a high-stakes venture. Fortunately, using the above strategies, you can improve the odds of getting accurate, timely, and valuable data backed by solid evidence.
Do you have plans for an upcoming executive retreat that involves strategic decision-making backed by AI data? If so, contact Gavel International to see how working with a meeting planning company can benefit your organization.
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SOURCE(S):
1 https://www.v500.com/accurate-ai/
