Dean Chester is a cybersecurity expert.
Artificial Intelligence (AI) tools and resources have become indispensable to today’s industry. The 2019 study by Gartner shows that in the last four years, the use of AI has increased by 270%. In the last year alone, the number of organizations that have deployed AI in some way has more than triples from 4% to 14%.
Why is AI becoming so popular with businesses of all sizes? Because AI tools produce considerable value and benefits for them. And this is now a proven fact.
Early AI adopters were bullish about the cognitive technologies in Deloitte’s 2017 cognitive survey. As many as 83% of companies stated that that the use of AI tools had generated ‘moderate’ or ‘significant’ benefits for them. In the 2018 survey, Deloitte found that these early adopters are ramping up their AI investments and getting positive returns.
Harvard Business Review agrees that Artificial Intelligence is reshaping the business. It estimates that over the next decade, the AI market will grow to $13 trillion. Companies that deployed AI for sales were able to:
- increase their leads by 50%,
- reduce their call time by 60-70%, and
- reduce their costs by 40-60%.
AI can empower sales reps by monitoring different signals and predicting a specific lead’s readiness to purchase. It can mine review sites, online communities, and social media platforms for buying signals and relate them with demographic and other types of information to find sales-ready leads. This alone can help small businesses increase the efficiency of their sales staff significantly.
Use AI-powered Data Analytics Tools
When we talk about machine learning, data science, or artificial intelligence, our attention is focused on huge enterprises. The truth is that whether a company is big or small, it needs data analytics tools that can:
- reduce its customer acquisition cost,
- improve its sales forecasting,
- help it capture the market share, and
- solve logistics problems.
AI tools allow small businesses to analyze data with lean resources.
Smaller and newer businesses have the liberty to gear towards data-driven decision-making from the start. In times when markets and customers are changing rapidly, it is almost suicidal for a business to stick to traditional business practices that are based on whims and fancies of the upper management.
Simple AI technologies today can help data scientists and business analysts work together to:
- connect to market data in real-time,
- clean it quickly, and
- use machine learning models for predictive analysis.
Free Best Data Analytics Tools for Small Businesses
Google Analytics: This free analytics platform offers various insights about user traffic on your website. It offers traffic reports that can help a small business:
- track user trends,
- identify the conversion points on the website,
- check the referrals and the traffic they direct to your website, and
- analyze keywords used by potential buyers to reach your website.
You may also embed tracking codes on your website to know more about the visitors on your website and gain some useful insights about them.
MS Excel: Excel is one of the most underrated but widely used tools for small-scale analytics. You can use graphs, pivot tables, and set up formulae to analyze data in your way. It is an ideal solution for a small business with low data volumes.
Qlik Sense: This is a free service for up to five users. You have to pay to allow more users to access it. This Business Intelligence tool creates a report by combining all your data sources at once place. It has a cloud-based version too. You can also create custom apps using it for your business intelligence requirement.
Tableau Public: This free service allows anyone to publish interactive data visualizations on the web. These vizzes can be embedded into web pages ad blogs or shared through social media or email. You do not require programming skills to use it.
The paid version of the tool can query:
- relational databases,
- OLAP (Online Analytical Processing) cubes,
- cloud database, etc.
and converts them into interactive dashboards.
Turn your Salespeople into Advisors with AI-powered Solutions
AI can fill in the roles of sales professionals:
- who take customer orders and process them
- provide information about different products to customers.
Sales reps of the future can take on the role of consultants and advisors with the help of AI. By analyzing customer data, they will be able to:
- identify the pain points of the customers,
- find out their reasons for buying a product, and
- identify who are the decision-makers in the deal.
Thus, they can have more engaging and relevant conversations with potential buyers.
The comprehensive data analytics AI systems today can use internal data as well as data collected from various sources to produce:
- actionable reports,
- sort information by date, geographic location, product lines, pricing structure, etc., and
- present business and marketplace opportunities to guide the management.
Small companies hesitate to adopt new AI and data science technologies because they lack adequate funds and resources. But today, the optimal use of revolutionary and innovative AI tools can allow small business owners to save a lot of money on product development, customer service chatbots sales IVR system, and marketing CRM. The key to success with AI applications is to align them with their respective business goals and create a long-term scalable plan for the future.
Keep Your Data Safe
AI platforms are an excellent choice for small businesses that do not have funds to set up their office or infrastructure yet. For example, VPN allows a small business owner to work from the nearest Starbucks on an encrypted connection – away from the prying sight. The employees working from remote locations can share files, link to record and program servers, and participate in video conferencing among many other things.
The reason so many apps and websites offer free services to people are to harvest their data to influence users in different ways. In 2018, the Cambridge Analytica (CA) scandal demonstrated how the Facebook account data of UK users were used to influence the outcome of the Brexit voting process.
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