Seven Factors To Consider Before Purchasing A Machine

Machine learning optimization continues to expand its capabilities throughout the business world. Before you sign on to begin using the latest and greatest technology tools, make sure you have a solid understanding of how the upgraded platform will address your team’s pain points and help you close on potential sales deals more efficiently.

Here are seven questions Forbes Business Development Council members suggest leaders think about to get the best return on their investment.

1. ‘Will Business Metrics Be Measurable?’

ROI will usually be the go-to metric, however, it may not necessarily be the most important for leadership. I suppose machine learning (ML) also comes with costs associated with it in terms of deployment, although it is important to consider how these compare to the costs of your old non-ML approach. At the end of the day, ML solutions need to boost business metrics for anyone to take notice. – Manny Reyna, Consultarian

2. ‘How Will It Empower The Sales Team?’

First, emphasize the point that machine learning does not replace sales reps; it simply gives them tools and data to maximize results. Some benefits the ML tools must provide to make sense are reducing the time spent on cumbersome tasks and streamlining the proposal or onboarding. As efficiency rises, they’ll have more time to enjoy the best part of sales: closing deals and meeting with customers. – James Mull, htmull

3. ‘Can The Company Support All Aspects Of The ML Platform?’

You can get started easily with machine learning if you have enough data, a case study idea and someone who knows Python. It takes experience, however, to know what use cases to prioritize and to ensure that the output is safe for the decision-making process. Other pitfalls are whether or not the ML models are supportable and scalable. Consider engaging experts for any major revamp. – Serrah Linares, Change Healthcare

4. ‘What Are The Digital Capabilities For Trends And Insights?’

The best bet on machine learning for the sales department is focusing on sales conversations. Most sales touch points are now digital. Sales teams can use machine learning to get conversion trends or forecasts, craft segment-specific messages or even train salespeople. This can help you leverage digital technologies to ace your key account management game. – Milind Katti, DemandFarm

5. ‘Which Digital Analytics Tools Will Best Serve Your Team?’

Start small because your team will not adopt every AI or ML tool in one day. A good place to begin is with a digital assistant powered by AI that serves as an omnipresent companion for salespeople and leverages analytics to provide advice on the next best action to take. This will enable the sales team to eliminate the guesswork from their engagements and instead refocus on building stronger relationships with their buyers. – Hayden Stafford, Seismic


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6. ‘What Are Your Goals And Expectations?’

ML revamps require three things to get started: good data hygiene as the foundation, a clear understanding of your current pain points and a vision of the expected results. Once you have these in place, an AI or ML engine can empower sales teams with the right insights, such as customer buying behavior, untapped revenue opportunities and better-aligned forecasts. – Danny Asnani, rSTAR Technologies

7. ‘Is The Sales Data Comprehensive And User-Friendly?’

Armed with an excellent understanding of the product, your target audience(s) and the current mediums with which you communicate, you will need comprehensive data on each of those three aspects of sales. In addition, you must be informed about the information contained within the data sets. Over time, use the AI analysis of those data sets to set applicable objectives for sales, fine-tuning the AI as you go. – Peter Schravemade, REACH ASEA

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