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Sales AI Implementation: A Complete Guide for Sales Operations

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A Forrester report shows that 46% of companies are looking to implement artificial intelligence (AI) into their marketing and sales teams.

So what does that mean for sales operations? They’ve been dubbed the leaders to take charge of AI implementation. If you’ve clicked on this guide, you’re likely aware of the benefits of AI and somewhat educated on what it is, but need some guidance on how to start the process.

AI is not like other “productivity tools” that can easily be ripped and replaced from the sales tech stack. Administering an AI tool requires thinking about your company’s long term goals and implementing accordingly.

Last year, more than half of business AI application efforts were stalled due to a lack of organizational readiness. To prevent your efforts from getting delayed, it’s important to be prepared and pragmatic when looking for an AI solution. We’re here to help.

Before Sales AI Implementation

Ahead of implementing AI into your sales organization, there’s a laundry list of things you should do before you even speak to a vendor or research various platforms.

This includes making a plan for sales AI implementation and assessing the current state of your sales data.

Create a strategy

Only one in three enterprise projects succeed, according to Forrester. Too often businesses rush to implement tools without stopping to strategically consider if they will solve their biggest problems just to get a solution in place. However, this will not bring favorable results. AI systems are complex and require time, effort and strategy to be successful.

Soon, every company will be using AI to improve business processes. When looking to employ into your own organization, don’t think of it as a “quick-fix” as these technologies will have a long-term impact on efficiency and productivity.

It’s up to sales operations to guarantee that this doesn’t happen with sales AI by creating an implementation plan.

When writing out a sales AI implementation strategy, consider the following:

  • Short and long term objectives
  • Current KPIs and if those will need to change
  • Current data quality and how it may need to be improved before implementation
  • A rough timeline of milestones
  • Obstacles that may prevent or delay implementation
  • Who will own this technology (sales ops, CRM administrator, IT, sales engineer, etc.)
  • Installation and onboarding
  • Trainings for end-users
  • Review sessions to continue optimization efforts

Bringing a complex AI platform into play may seem daunting, but taking the right steps in small increments will lead to a positive end result.

Audit Sales Data for Quality

Having robust, accurate data is essential prior to implementing sales AI. In order for any sales AI or ML system to produce results, it must learn from the mountain of customer data that exists in an organization’s CRM (or other sales database).

First, perform an audit of your data and consider these three things: data quality, data collection and storage and lastly, security.

When it comes to data quality, it’s vital that data is clean. AI uses data to make predictions, therefore if the sales data is inaccurate it will produce inaccurate results.

Assess how much data is missing or inaccurate. For example, if lead title or phone number fields are often left blank or if there are too many variations of a company name. Consider whether the AI system could function properly and bring the desired results with the current state of the sales data.

Cleanliness of data in itself can be a major business problem that AI can solve. If this is the case, consider using an AI solution with a data cleanliness component to increase data accuracy.

Second, examine the data storage and collection process. Unfortunately, in many organizations, customer and sales data exists in several siloed locations. Perhaps some information exists in the CRM or database, others only in spreadsheets, or emails. This is a problem as it prevents your organization from seeing a complete view of the sales process and pipeline.

Locate all the data related to the sales organization and decide where that data should be centralized.

And finally, consider security. Customer and business data should be kept under tight lock and key, both for the benefit of the company and its customers. No system should ever remove or have access to any of your sensitive data.

Have a rough idea of how strict your platform will need to be on security before implementation. Talk to your legal and IT teams to get a better understanding of what types of security a platform needs to have.

Navigating Sales AI Vendors

Now you’re ready to research potential solutions. Unfortunately, this can be more difficult that it may seem.

Sales tools are making their way into the market at an accelerated pace. As of mid-2018, there were over 800 sales tech tools on the market, up 25% from the year before. The number of sales tech tools is only expected to increase, however few are either fundamentally based on AI technology or just starting to integrate AI components.

It’s important to narrow down this market and focus on the sales AI tools that will improve the effectiveness of your team long term.

Understanding the Sales AI Market

Before reaching out to vendors,  research the problems your current sales team is facing or the goal you’d like to achieve in implementing AI. See what tools are out there and create a short list (four to six vendors maximum).

There are dozens of sales AI tools out there, but we group them into six categories. Here’s how we break down the current sales AI market.

  1. Sales automation

Automation involves having an AI tool perform low-level, repetitive tasks automatically with little assistance from the sales rep. Tasks that could be automated include CRM data entry, prospecting and researching, scheduling meetings, drafting emails, etc.

  1. Predictive engagement

Predictive engagement guides reps in the right direction. Think “next-step” analytics that coaches them on what to do with a certain lead/prospect next. This could be suggesting they send certain types of content or reminding them to follow up on a certain day and time.

  1. Predictive prospecting

Predictive prospecting helps sort through opportunities and leads. Prospecting tools can automate the lead scoring process and find relevant customers that fit specified parameters.

  1. Sales process analytics

While these tools focus on more traditional analytics, they still bring a ton of value to sales organizations by analyzing rep behavior then generating reports based on KPIs or offer suggestions to improve processes. Basically, these keep sales leaders in tune with what activities their reps are focusing on and assist in optimizing the sales process.

  1. Voice/Text analytics

These tools observe and report on sales reps’ conversations or emails with customers to improve communication skills and increase conversion rates.

  1. Chatbots

Chatbots are designed to replicate human conversation using NLP and are traditionally used to help with customer service or prequalification.

Asking the Right Questions

Next, it’s time to make contact and ask the right questions to the vendors on your short list.

You’ll need to get an understanding of the product, processes, ROI and implementation/installation steps as you begin to narrow down the potential solutions. Here are some questions to ask every provider on your short list.

  • “What use cases does your product offer?”

Make sure any solution you’re considering solves your specific business problems. There are hundreds of sales tools out there with varying use cases, but no tool can do it all. Pinpoint your largest problems and don’t waste your time talking to vendors that don’t solve them.

  • “How will this affect my current sales process?”

Does this add a new step to your sales reps’ process or does it eliminate one? The goal with AI implementation is to streamline and make your reps’ job easier. If a tool will add a step to your process, really evaluate the other value it will bring your organization and if it is worth changing your current processes.

  • “How will this product integrate with my current sales tools?”

Will this product work with the tools that you already have? If you need a certain CRM or external tool in order for it to work, you’ll need to know that up front. Implementing just one new tool can greatly affect a sales team, but if your reps will need to change how they work with multiple tools in order to use an AI solution, consider overall ROI and if it’s valuable enough to adjust your entire tech stack.

  • “What is the installation process?”

Is it easy to install? Does IT need to be involved? Who needs to service the product? Does each unit need to be set up individually and/or independently? It’s important to know what it will take to get the product up and running. Identify the stakeholders and teams who will need to assist in installation and get a rough timeline on how long this step will take.

  • “What is the learning curve for the end user?”

Will your teams need to be formally trained or is the solution simple and straightforward to use? It’s important that you know the complexity, how user-friendly the UI is and how much effort and time it will take for your team to be productive. Also, ask if they offer any training or onboarding programs.

  • “What types of data or tools does your product need to operate successfully?”

As you narrow down your shortlist to one or two solutions, it’s important to ask your potential provider what they’ll need from you in order to get the trial or PoC up and running. Most AI tools require data sets to learn from, and to demonstrate results. Here are some follow-up questions that will give you a better idea of what you might need:

  • “Which types of data does this solution need to have access to?”
  • “Which existing sales tools need to be integrated with this tool?”
  • “Do I need to perform a data audit/clean up ahead of AI implementation?”

Asking these critical questions before your sales AI system is installed will save you lots of trouble later.

  • “What security measures are built into your product?”

Ensure that both your confidential business data and the data of your customers are under tight lock and key. There are all kinds of security measures that a company could take, whether it be unique encryption keys, blockchain or blind data. Make sure you fully understand their security measures, that no human will have access to your information (unless explicitly granted by you) and that the AI system will not pull data into external systems or databases unless requested.

  • “What are the next steps for implementation?”

Every solution has a different implementation process and steps that need to be taken to get the ball rolling. For example, at Automation Hero we ask for a point of contact, host a Use Case Discovery Workshop to help an organization discover its highest value, lowest effort use cases and then agree to PoC terms based on that workshop. Having an understanding of what comes next helps your organization quickly adjust and adopt this technology and you start seeing results sooner rather than later.

Use these questions to narrow down your shortlist to a single vendor. Always consider your biggest inefficiencies when picking a solution.

Installation and Integration

At this point you’ve got an AI solution lined up and the plan to implement it is in motion. Where do you go from here?

Take inventory of the tools and processes the sales team has in place. Consider how this new solution will need to be integrated with them. Does it need to be hooked up to your CRM? Does it need to be installed on the desktop or as a web application on your rep’s computers? Will your team need login information?

Create a checklist of all the items and systems that will need to be installed and integrated with your new sales AI solution. Then make a list of people or teams that will need to assist in the installation process. Ownership during installation will be key.

Begin this step by aligning all stakeholders. Consider the different “owners” of information and technical implementation. Does IT need to be involved to install the software? Does legal need to sign-off on the security measures? Does a Salesforce admin need to be sure that the product can be customized?

List out all stakeholders that will need to sign-off in order to move the project forward. Doing this ahead of time will help you see where there might be potential roadblocks and to ensure you have the support you’ll need within your organization. Sales reps may need to verify their email.

Don’t leave anything out when creating this list to ensure that you’re not blindsided by an unexpected implementation or installation step.

Preparing People

And finally, make sure the entire sales organization is ready and aligned before the AI system is in place. Create a change management plan that gets everyone on board with this initiative.

The sales reps (or other end-users) need to have an understanding of this project and how it will bring value to their role. Otherwise, they will be less motivated to use the technology correctly and consistently.

Be sure they understand what is required of them through each onboarding phase. For example, there will likely be test users that will need to provide feedback so make sure they understand why feedback is important and what type is needed.

Once the AI platform is purchased and implemented, train all individuals on how to properly use it. This will need to be ongoing and built into your onboarding process. Included in this training should be what the KPIs are to measure success and if their own KPIs will change because of its implementation.

Change management is critical when implementing a new piece of technology, especially one that will be taking over daily tasks for your sales reps. As the implementation initiator, it’s important to walk your organization through the process in its entirety to ensure it’s successful.

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