How machine learning will impact your sales processes
There is no denying the fact that technology has developed at a rapid pace over the past few years, and this is something that shows no signs of slowing down. These innovations and advancements are changing the way that we handle business in our 24/7 world. They are impacting everything from our marketing campaigns to how we interact with existing customers. If your business is to stay ahead of the game and reap all of the rewards associated with these types of technology, you need to stay ahead of everything that is going on in the industry. At the moment, machine learning is playing a huge role. With that being said, below we are going to take a look at some of the different ways that machine learning is impacting how we go about targeting new potential customers.
- Reinforcement learning for marketing decisions that are sequential - Some of the most difficult and complicated decisions we make are not single predictions. Rather, they are a number of different decisions that we make over a long period of time. Balancing long-term gains with short-term tradeoffs is a challenge for even the most intelligent of humans. This is where machine learning can come in.
- Superior reporting - Another way in which machine learning ables you to target new customers more effectively is because it provides enhanced reporting capabilities through automated data visualisation. After all, images speak louder than words. Not only is AI faster but it is more efficient when it comes to the transformation of data into visual insight. Automated enterprise analytics solutions will become the norm instead of sing tools like Tableau and Excel. These software options can generate useful dashboards and centralise data sources, resulting in helpful and easy-to-understand reports for your marketing teams.
- Branded object recognition - When it comes to AI and machine learning, there is no denying that computer vision is a field that is rapidly advancing at the moment. It lends itself to a broad scope of applications. Marketing teams will be able to utilise machine learning powered computer vision so that products can be recognised and so that user insight can be extracted from unlabeled videos and images. This means that businesses will have the capacity to determine when their logos have appeared in content that has been user-generated. You can then calculate quickly and easily the media that has been earned by using video analysis.
- Speech-To-Text (STT) and Text-To-Speech (TTS) to power searches that are voice-based - Voice-only and voice-enabled platforms have introduced a new paradigm and new possibilities when it comes to user engagement for our hardware and software interfaces. When you consider the fact that voice-based digital assistants are on the rise, such as Google Assistant and Amazon Echo, you understand that shopping is becoming more and more touch-free. This enhances the convenience associated with online shopping, which is what the Internet is all about. In order to future-proof your marketing, you are going to need to have a conversational AI strategy.
- Customer experience automation and dialog systems for chatbots - Aside from the areas of improvement that have already been mentioned, another domain that machine learning has had a massive impact on is with regards to chatbots and bots. This area represents one of the most ubiquitous applications of machine learning. However, the vast majority of the marketing bots today use minimal machine learning and natural language processing. Instead, they are completely scripted. This can, in fact, causes frustration for the consumer because they know they are dealing with a bot instead of a consumer and then scripted responses can often offer nothing of any value. However, we are now going to see more sophisticated dialog systems being used, and this is definitely something that you should be able to look into. These bots will have the capability to transfer to a human agent when needed, adapt to unusual questions, and reference external knowledge bases. There are a number of businesses today that have already adopted chatbots so that customers can be engaged throughout their lifecycle. This means that they will be engaged from the moment they learn about the brand right through to the point whereby they need customer support after they have made a purchase.
- Text classification for user personalisation and insight - A machine learning system can utilise natural language processing (NLP) so that it can probe voice or text-based content. This will then be classified based on a number of different variable factors. This includes everything from topic to sentiment and tone. This will ensure that the relevant materials are cultivated and the right customer insight is generated.
- Dynamic pricing through the use of regression models - In addition to all of the marketing benefits associated with machine learning that have already been mentioned, it is also important to touch on regression models for dynamic pricing. There is no denying that the pricing scheme you choose can be the difference between a product that is a success and one that isn’t. Regression techniques enable marketing teams to predict numerical values that are based on features that already existed, which will then mean they have the power to optimise different elements of the consumer journey. This can be utilised when it comes to the optimisation of your marketing spend as well, as well as being used for sales forecasting.
All in all, there is no denying that machine learning is playing a massive role when it comes to marketing today and the way in which we are going about targeting customers. With that being said, if your business is to stay ahead of the game and have a marketing campaign that is truly effective in the digital age, you need to take note of everything that has been discussed above. Machine learning can enhance your marketing efforts in many different ways, and so it is imperative that you take advantage of this.