Zoho Creator is a useful and versatile platform. One of the more common requirements, especially when creating a new app, is to import data. While it has a decent import tool there is a limitation worth noting.
Using Numbers on a Mac I was unable to select a Numbers date format which was compatible with the Zoho form date format. The format is dd-MMM-yyyy. This cannot be changed – or I couldn’t easily find where to change this. Numbers does not support this format. As a result I had to use Google sheets.
When measuring adoption it’s useful to see the number of logged in users for a given period as a percentage of the total user base. Since Salesforce reports can only report on what data is visible (as is to be expected) it’s not possible to compare logged in users to total users. There is a way around this by using a joined report.
- Create a joined report using User as the primary object. This will create a Users block.
- Use a common field and drag it over to an empty space in the preview area. This will create a second Users block. Filter this block on logged-in users for the desired timeframe.
- Create a cross-object formula field using the Record Count summary fields.
One of the more painful administrative tasks faced by Sales reps and account managers is keeping contact lists up to date. Sure, many platforms offer mail and calendar integration but there is still some work to be done, i.e. the contact has to be loaded in the contact application, such as Outlook, before it can be added as a Contact in the CRM platform.
Recently, Apple introduced a feature whereby, an incoming caller number is tagged with a potential contact name based on iOS matching the incoming number with a number in the email signature of an exchange with the contact.
Salesforce Einstein provides a similar benefit which is called Automated Contacts.
This is a simple but beneficial time-saving device which highlights the benefits of embedded AI technologies in a CRM platform
CRM vendors are increasing their investments in AI technology and making it available in their CRM platforms to support decision making and to trigger actions.
AI encompasses machine learning and deep learning as well data science methods. It is closely linked to the field of data analytics.
AI is about thinking machines. Data is ingested and patterns are detected using statistical models. These patterns can be used to predict behaviour and a host of other outcomes.
These benefits include predictive scoring (lead scoring), forecasting (predict future revenue), recommendations (for cross sell purposes) and early warning systems (for retention). In other words, AI will eclipse what generic algorithms offer, will enhance salespersons’ intuition and will intelligently monitor customer activities.
Other benefits include chatbots, virtual customer assistants, intelligent social media monitoring and automatically logging customer interactions.
Having made the investments the software marketing machines are kicking into high gear so there is an element of hype. However, the benefits for successful early adopters could be significant so be on the look-out for opportunities to experiment with the ever-expanding and quickly maturing AI toolset.
Finally, as always, as with all things CRM the quality of the data will make the difference between a mediocre outcome and a great outcome.
CRM (Artificial Intelligence) AI vendors and tools include:
- Conversica – automated sales assistants
- Introhive – data automation and sales acceleration
- Salesforce.com Einstein – AI built into Cloud products
- DigitalGenius – automate customer service
- Microsoft Cortana – marketing, sales and service analytics solutions
Resistance to CRM adoption can be overcome by satisfactorily answering a number of key questions.
Answering the ‘What’s in it for me?’ question. This implies demonstrating the value and utility of the CRM application. In other words it’s about ensuring that the CRM implementation addresses recognised business needs. Answering this question is fundamental to successful adoption as it facilitates the buy-in and embedment process.
Have users at all levels been involved in the initial and ongoing design? This is important to build a sense of ownership, overcome us versus them thinking and incorporating the ‘what’ and ‘how’ aspects of the application. Many times a solution design which does not involve users will meet the requirements but not in the way that the impacted users expect the requirement to be addressed which means that their experience will be less than optimal and usage will suffer. This must also, importantly, address expectations of how data will be captured, processes will be made easier and data from other systems will be surfaced in the CRM application.
Has the change been communicated effectively and is there evidence that it has been understood in the context of the impact on users current way of doing things? Often overlooked, communicating the rationale for and positive impact of the CRM application will reduce noise, aid adoption and align expectations.
Is there adequate training material across a variety of training modalities? Good training and related training material are essential to overcome the initial friction users will experience when starting to use the CRM application. It’s frustrating when starting to use an application for the first time and not having the right training guides readily available. It’s also beneficial to make liberal use of inline help and context aware help tools.
How will data quality be managed? The single biggest inherent risk to the success of a CRM application is poor data quality. Poor data quality seriously undermines the credibility of the application and will retard adoption and usage. Data quality should address accuracy, completeness, relevancy and currency of data.
How will ongoing enhancements and support be managed? Effective CRM applications evolve with business and user needs. Enhancements ensure that the application remains relevant to the business, smooths over user frustrations and aids with maintaining good data quality. A good support model addresses support resource constraints, user issues, provides useful input to training content and potentially reduces commonly occurring issues by implementing enhancements to address these issues.
CRM in the Cloud or Cloud services refers to CRM software applications which are hosted on the Web and made available through a Web Browser.
In this way there is no need to manage hardware and software on premise.
Big data, in the context of CRM, relates to large volumes of data used for (mostly predictive) analytics.
Data can be collected from various sources including customer channels, transactions and other customer activities such as product usage.
By applying analytics to these large volumes of data customer patterns, associations and trends can be identified. This can then be used to predict behaviours and outcomes.
Benefits can include better decision making, predictive modeling, and benchmarking.
This means that, for example, Marketing, Sales or Service reps can be equipped with insights to identify hot leads, close sales faster, predict when service issues can blow up.
CRM vendors include:
- Microsoft CRM Dynamics (online and on-premise solutions)
- SAP CRM & Cloud for Sales
- Oracle (Sales Cloud & Siebel CRM)
- Zoho CRM (Free / Community version available)
- SugarCRM (Free / Community version available)
- SuiteCRM (Open source CRM – Sugar CRM fork)
- Capsule CRM
- AgileCRM (Free / Community version available)
- You don’t need a CRM
- Pipeliner CRM
- Capsule CRM
- Odyssey CRM
- vTiger (Free / Community version available)
- Zurmo (Free / Community version available)
- Highrise CRM
- Skyward CRM
- Really Simple Systems (Free / Community version available)
- Batchbook CRM
- Fat Free CRM (Open source CRM)
- Hubspot CRM (Free version)
- EspoCRM (Open source CRM)
- Oro CRM (Open source CRM)
Many of the above applications are suitable for small businesses and SMEs
CRM Service relates to all aspects of managing post-sales customer support issues including:
- Logging cases or tickets across multiple channels (including call centres)
- Managing service level agreements and escalations
- Field service management
- Social media management
CRM Marketing refers to tools or features which automate or help manage marketing processes.
This could include:
- Campaign management
- Lead management
- Web and social media management
- Multi-channel customer journey management