<?php
/**
 * Network API: WP_Network_Query class
 *
 * @package WordPress
 * @subpackage Multisite
 * @since 4.6.0
 */

/**
 * Core class used for querying networks.
 *
 * @since 4.6.0
 *
 * @see WP_Network_Query::__construct() for accepted arguments.
 */
#[AllowDynamicProperties]
class WP_Network_Query {

	/**
	 * SQL for database query.
	 *
	 * @since 4.6.0
	 * @var string
	 */
	public $request;

	/**
	 * SQL query clauses.
	 *
	 * @since 4.6.0
	 * @var array
	 */
	protected $sql_clauses = array(
		'select'  => '',
		'from'    => '',
		'where'   => array(),
		'groupby' => '',
		'orderby' => '',
		'limits'  => '',
	);

	/**
	 * Query vars set by the user.
	 *
	 * @since 4.6.0
	 * @var array
	 */
	public $query_vars;

	/**
	 * Default values for query vars.
	 *
	 * @since 4.6.0
	 * @var array
	 */
	public $query_var_defaults;

	/**
	 * List of networks located by the query.
	 *
	 * @since 4.6.0
	 * @var array
	 */
	public $networks;

	/**
	 * The amount of found networks for the current query.
	 *
	 * @since 4.6.0
	 * @var int
	 */
	public $found_networks = 0;

	/**
	 * The number of pages.
	 *
	 * @since 4.6.0
	 * @var int
	 */
	public $max_num_pages = 0;

	/**
	 * Constructor.
	 *
	 * Sets up the network query, based on the query vars passed.
	 *
	 * @since 4.6.0
	 *
	 * @param string|array $query {
	 *     Optional. Array or query string of network query parameters. Default empty.
	 *
	 *     @type int[]        $network__in          Array of network IDs to include. Default empty.
	 *     @type int[]        $network__not_in      Array of network IDs to exclude. Default empty.
	 *     @type bool         $count                Whether to return a network count (true) or array of network objects.
	 *                                              Default false.
	 *     @type string       $fields               Network fields to return. Accepts 'ids' (returns an array of network IDs)
	 *                                              or empty (returns an array of complete network objects). Default empty.
	 *     @type int          $number               Maximum number of networks to retrieve. Default empty (no limit).
	 *     @type int          $offset               Number of networks to offset the query. Used to build LIMIT clause.
	 *                                              Default 0.
	 *     @type bool         $no_found_rows        Whether to disable the `SQL_CALC_FOUND_ROWS` query. Default true.
	 *     @type string|array $orderby              Network status or array of statuses. Accepts 'id', 'domain', 'path',
	 *                                              'domain_length', 'path_length' and 'network__in'. Also accepts false,
	 *                                              an empty array, or 'none' to disable `ORDER BY` clause. Default 'id'.
	 *     @type string       $order                How to order retrieved networks. Accepts 'ASC', 'DESC'. Default 'ASC'.
	 *     @type string       $domain               Limit results to those affiliated with a given domain. Default empty.
	 *     @type string[]     $domain__in           Array of domains to include affiliated networks for. Default empty.
	 *     @type string[]     $domain__not_in       Array of domains to exclude affiliated networks for. Default empty.
	 *     @type string       $path                 Limit results to those affiliated with a given path. Default empty.
	 *     @type string[]     $path__in             Array of paths to include affiliated networks for. Default empty.
	 *     @type string[]     $path__not_in         Array of paths to exclude affiliated networks for. Default empty.
	 *     @type string       $search               Search term(s) to retrieve matching networks for. Default empty.
	 *     @type bool         $update_network_cache Whether to prime the cache for found networks. Default true.
	 * }
	 */
	public function __construct( $query = '' ) {
		$this->query_var_defaults = array(
			'network__in'          => '',
			'network__not_in'      => '',
			'count'                => false,
			'fields'               => '',
			'number'               => '',
			'offset'               => '',
			'no_found_rows'        => true,
			'orderby'              => 'id',
			'order'                => 'ASC',
			'domain'               => '',
			'domain__in'           => '',
			'domain__not_in'       => '',
			'path'                 => '',
			'path__in'             => '',
			'path__not_in'         => '',
			'search'               => '',
			'update_network_cache' => true,
		);

		if ( ! empty( $query ) ) {
			$this->query( $query );
		}
	}

	/**
	 * Parses arguments passed to the network query with default query parameters.
	 *
	 * @since 4.6.0
	 *
	 * @param string|array $query WP_Network_Query arguments. See WP_Network_Query::__construct() for accepted arguments.
	 */
	public function parse_query( $query = '' ) {
		if ( empty( $query ) ) {
			$query = $this->query_vars;
		}

		$this->query_vars = wp_parse_args( $query, $this->query_var_defaults );

		/**
		 * Fires after the network query vars have been parsed.
		 *
		 * @since 4.6.0
		 *
		 * @param WP_Network_Query $query The WP_Network_Query instance (passed by reference).
		 */
		do_action_ref_array( 'parse_network_query', array( &$this ) );
	}

	/**
	 * Sets up the WordPress query for retrieving networks.
	 *
	 * @since 4.6.0
	 *
	 * @param string|array $query Array or URL query string of parameters.
	 * @return array|int List of WP_Network objects, a list of network IDs when 'fields' is set to 'ids',
	 *                   or the number of networks when 'count' is passed as a query var.
	 */
	public function query( $query ) {
		$this->query_vars = wp_parse_args( $query );
		return $this->get_networks();
	}

	/**
	 * Gets a list of networks matching the query vars.
	 *
	 * @since 4.6.0
	 *
	 * @return array|int List of WP_Network objects, a list of network IDs when 'fields' is set to 'ids',
	 *                   or the number of networks when 'count' is passed as a query var.
	 */
	public function get_networks() {
		$this->parse_query();

		/**
		 * Fires before networks are retrieved.
		 *
		 * @since 4.6.0
		 *
		 * @param WP_Network_Query $query Current instance of WP_Network_Query (passed by reference).
		 */
		do_action_ref_array( 'pre_get_networks', array( &$this ) );

		$network_data = null;

		/**
		 * Filters the network data before the query takes place.
		 *
		 * Return a non-null value to bypass WordPress' default network queries.
		 *
		 * The expected return type from this filter depends on the value passed
		 * in the request query vars:
		 * - When `$this->query_vars['count']` is set, the filter should return
		 *   the network count as an integer.
		 * - When `'ids' === $this->query_vars['fields']`, the filter should return
		 *   an array of network IDs.
		 * - Otherwise the filter should return an array of WP_Network objects.
		 *
		 * Note that if the filter returns an array of network data, it will be assigned
		 * to the `networks` property of the current WP_Network_Query instance.
		 *
		 * Filtering functions that require pagination information are encouraged to set
		 * the `found_networks` and `max_num_pages` properties of the WP_Network_Query object,
		 * passed to the filter by reference. If WP_Network_Query does not perform a database
		 * query, it will not have enough information to generate these values itself.
		 *
		 * @since 5.2.0
		 * @since 5.6.0 The returned array of network data is assigned to the `networks` property
		 *              of the current WP_Network_Query instance.
		 *
		 * @param array|int|null   $network_data Return an array of network data to short-circuit WP's network query,
		 *                                       the network count as an integer if `$this->query_vars['count']` is set,
		 *                                       or null to allow WP to run its normal queries.
		 * @param WP_Network_Query $query        The WP_Network_Query instance, passed by reference.
		 */
		$network_data = apply_filters_ref_array( 'networks_pre_query', array( $network_data, &$this ) );

		if ( null !== $network_data ) {
			if ( is_array( $network_data ) && ! $this->query_vars['count'] ) {
				$this->networks = $network_data;
			}

			return $network_data;
		}

		// $args can include anything. Only use the args defined in the query_var_defaults to compute the key.
		$_args = wp_array_slice_assoc( $this->query_vars, array_keys( $this->query_var_defaults ) );

		// Ignore the $fields, $update_network_cache arguments as the queried result will be the same regardless.
		unset( $_args['fields'], $_args['update_network_cache'] );

		$key          = md5( serialize( $_args ) );
		$last_changed = wp_cache_get_last_changed( 'networks' );

		$cache_key   = "get_network_ids:$key:$last_changed";
		$cache_value = wp_cache_get( $cache_key, 'network-queries' );

		if ( false === $cache_value ) {
			$network_ids = $this->get_network_ids();
			if ( $network_ids ) {
				$this->set_found_networks();
			}

			$cache_value = array(
				'network_ids'    => $network_ids,
				'found_networks' => $this->found_networks,
			);
			wp_cache_add( $cache_key, $cache_value, 'network-queries' );
		} else {
			$network_ids          = $cache_value['network_ids'];
			$this->found_networks = $cache_value['found_networks'];
		}

		if ( $this->found_networks && $this->query_vars['number'] ) {
			$this->max_num_pages = (int) ceil( $this->found_networks / $this->query_vars['number'] );
		}

		// If querying for a count only, there's nothing more to do.
		if ( $this->query_vars['count'] ) {
			// $network_ids is actually a count in this case.
			return (int) $network_ids;
		}

		$network_ids = array_map( 'intval', $network_ids );

		if ( 'ids' === $this->query_vars['fields'] ) {
			$this->networks = $network_ids;
			return $this->networks;
		}

		if ( $this->query_vars['update_network_cache'] ) {
			_prime_network_caches( $network_ids );
		}

		// Fetch full network objects from the primed cache.
		$_networks = array();
		foreach ( $network_ids as $network_id ) {
			$_network = get_network( $network_id );
			if ( $_network ) {
				$_networks[] = $_network;
			}
		}

		/**
		 * Filters the network query results.
		 *
		 * @since 4.6.0
		 *
		 * @param WP_Network[]     $_networks An array of WP_Network objects.
		 * @param WP_Network_Query $query     Current instance of WP_Network_Query (passed by reference).
		 */
		$_networks = apply_filters_ref_array( 'the_networks', array( $_networks, &$this ) );

		// Convert to WP_Network instances.
		$this->networks = array_map( 'get_network', $_networks );

		return $this->networks;
	}

	/**
	 * Used internally to get a list of network IDs matching the query vars.
	 *
	 * @since 4.6.0
	 *
	 * @global wpdb $wpdb WordPress database abstraction object.
	 *
	 * @return int|array A single count of network IDs if a count query. An array of network IDs if a full query.
	 */
	protected function get_network_ids() {
		global $wpdb;

		$order = $this->parse_order( $this->query_vars['order'] );

		// Disable ORDER BY with 'none', an empty array, or boolean false.
		if ( in_array( $this->query_vars['orderby'], array( 'none', array(), false ), true ) ) {
			$orderby = '';
		} elseif ( ! empty( $this->query_vars['orderby'] ) ) {
			$ordersby = is_array( $this->query_vars['orderby'] ) ?
				$this->query_vars['orderby'] :
				preg_split( '/[,\s]/', $this->query_vars['orderby'] );

			$orderby_array = array();
			foreach ( $ordersby as $_key => $_value ) {
				if ( ! $_value ) {
					continue;
				}

				if ( is_int( $_key ) ) {
					$_orderby = $_value;
					$_order   = $order;
				} else {
					$_orderby = $_key;
					$_order   = $_value;
				}

				$parsed = $this->parse_orderby( $_orderby );

				if ( ! $parsed ) {
					continue;
				}

				if ( 'network__in' === $_orderby ) {
					$orderby_array[] = $parsed;
					continue;
				}

				$orderby_array[] = $parsed . ' ' . $this->parse_order( $_order );
			}

			$orderby = implode( ', ', $orderby_array );
		} else {
			$orderby = "$wpdb->site.id $order";
		}

		$number = absint( $this->query_vars['number'] );
		$offset = absint( $this->query_vars['offset'] );
		$limits = '';

		if ( ! empty( $number ) ) {
			if ( $offset ) {
				$limits = 'LIMIT ' . $offset . ',' . $number;
			} else {
				$limits = 'LIMIT ' . $number;
			}
		}

		if ( $this->query_vars['count'] ) {
			$fields = 'COUNT(*)';
		} else {
			$fields = "$wpdb->site.id";
		}

		// Parse network IDs for an IN clause.
		if ( ! empty( $this->query_vars['network__in'] ) ) {
			$this->sql_clauses['where']['network__in'] = "$wpdb->site.id IN ( " . implode( ',', wp_parse_id_list( $this->query_vars['network__in'] ) ) . ' )';
		}

		// Parse network IDs for a NOT IN clause.
		if ( ! empty( $this->query_vars['network__not_in'] ) ) {
			$this->sql_clauses['where']['network__not_in'] = "$wpdb->site.id NOT IN ( " . implode( ',', wp_parse_id_list( $this->query_vars['network__not_in'] ) ) . ' )';
		}

		if ( ! empty( $this->query_vars['domain'] ) ) {
			$this->sql_clauses['where']['domain'] = $wpdb->prepare( "$wpdb->site.domain = %s", $this->query_vars['domain'] );
		}

		// Parse network domain for an IN clause.
		if ( is_array( $this->query_vars['domain__in'] ) ) {
			$this->sql_clauses['where']['domain__in'] = "$wpdb->site.domain IN ( '" . implode( "', '", $wpdb->_escape( $this->query_vars['domain__in'] ) ) . "' )";
		}

		// Parse network domain for a NOT IN clause.
		if ( is_array( $this->query_vars['domain__not_in'] ) ) {
			$this->sql_clauses['where']['domain__not_in'] = "$wpdb->site.domain NOT IN ( '" . implode( "', '", $wpdb->_escape( $this->query_vars['domain__not_in'] ) ) . "' )";
		}

		if ( ! empty( $this->query_vars['path'] ) ) {
			$this->sql_clauses['where']['path'] = $wpdb->prepare( "$wpdb->site.path = %s", $this->query_vars['path'] );
		}

		// Parse network path for an IN clause.
		if ( is_array( $this->query_vars['path__in'] ) ) {
			$this->sql_clauses['where']['path__in'] = "$wpdb->site.path IN ( '" . implode( "', '", $wpdb->_escape( $this->query_vars['path__in'] ) ) . "' )";
		}

		// Parse network path for a NOT IN clause.
		if ( is_array( $this->query_vars['path__not_in'] ) ) {
			$this->sql_clauses['where']['path__not_in'] = "$wpdb->site.path NOT IN ( '" . implode( "', '", $wpdb->_escape( $this->query_vars['path__not_in'] ) ) . "' )";
		}

		// Falsey search strings are ignored.
		if ( strlen( $this->query_vars['search'] ) ) {
			$this->sql_clauses['where']['search'] = $this->get_search_sql(
				$this->query_vars['search'],
				array( "$wpdb->site.domain", "$wpdb->site.path" )
			);
		}

		$join = '';

		$where = implode( ' AND ', $this->sql_clauses['where'] );

		$groupby = '';

		$pieces = array( 'fields', 'join', 'where', 'orderby', 'limits', 'groupby' );

		/**
		 * Filters the network query clauses.
		 *
		 * @since 4.6.0
		 *
		 * @param string[]         $clauses {
		 *     Associative array of the clauses for the query.
		 *
		 *     @type string $fields   The SELECT clause of the query.
		 *     @type string $join     The JOIN clause of the query.
		 *     @type string $where    The WHERE clause of the query.
		 *     @type string $orderby  The ORDER BY clause of the query.
		 *     @type string $limits   The LIMIT clause of the query.
		 *     @type string $groupby  The GROUP BY clause of the query.
		 * }
		 * @param WP_Network_Query $query   Current instance of WP_Network_Query (passed by reference).
		 */
		$clauses = apply_filters_ref_array( 'networks_clauses', array( compact( $pieces ), &$this ) );

		$fields  = isset( $clauses['fields'] ) ? $clauses['fields'] : '';
		$join    = isset( $clauses['join'] ) ? $clauses['join'] : '';
		$where   = isset( $clauses['where'] ) ? $clauses['where'] : '';
		$orderby = isset( $clauses['orderby'] ) ? $clauses['orderby'] : '';
		$limits  = isset( $clauses['limits'] ) ? $clauses['limits'] : '';
		$groupby = isset( $clauses['groupby'] ) ? $clauses['groupby'] : '';

		if ( $where ) {
			$where = 'WHERE ' . $where;
		}

		if ( $groupby ) {
			$groupby = 'GROUP BY ' . $groupby;
		}

		if ( $orderby ) {
			$orderby = "ORDER BY $orderby";
		}

		$found_rows = '';
		if ( ! $this->query_vars['no_found_rows'] ) {
			$found_rows = 'SQL_CALC_FOUND_ROWS';
		}

		$this->sql_clauses['select']  = "SELECT $found_rows $fields";
		$this->sql_clauses['from']    = "FROM $wpdb->site $join";
		$this->sql_clauses['groupby'] = $groupby;
		$this->sql_clauses['orderby'] = $orderby;
		$this->sql_clauses['limits']  = $limits;

		// Beginning of the string is on a new line to prevent leading whitespace. See https://core.trac.wordpress.org/ticket/56841.
		$this->request =
			"{$this->sql_clauses['select']}
			 {$this->sql_clauses['from']}
			 {$where}
			 {$this->sql_clauses['groupby']}
			 {$this->sql_clauses['orderby']}
			 {$this->sql_clauses['limits']}";

		if ( $this->query_vars['count'] ) {
			return (int) $wpdb->get_var( $this->request );
		}

		$network_ids = $wpdb->get_col( $this->request );

		return array_map( 'intval', $network_ids );
	}

	/**
	 * Populates found_networks and max_num_pages properties for the current query
	 * if the limit clause was used.
	 *
	 * @since 4.6.0
	 *
	 * @global wpdb $wpdb WordPress database abstraction object.
	 */
	private function set_found_networks() {
		global $wpdb;

		if ( $this->query_vars['number'] && ! $this->query_vars['no_found_rows'] ) {
			/**
			 * Filters the query used to retrieve found network count.
			 *
			 * @since 4.6.0
			 *
			 * @param string           $found_networks_query SQL query. Default 'SELECT FOUND_ROWS()'.
			 * @param WP_Network_Query $network_query        The `WP_Network_Query` instance.
			 */
			$found_networks_query = apply_filters( 'found_networks_query', 'SELECT FOUND_ROWS()', $this );

			$this->found_networks = (int) $wpdb->get_var( $found_networks_query );
		}
	}

	/**
	 * Used internally to generate an SQL string for searching across multiple columns.
	 *
	 * @since 4.6.0
	 *
	 * @global wpdb $wpdb WordPress database abstraction object.
	 *
	 * @param string   $search  Search string.
	 * @param string[] $columns Array of columns to search.
	 * @return string Search SQL.
	 */
	protected function get_search_sql( $search, $columns ) {
		global $wpdb;

		$like = '%' . $wpdb->esc_like( $search ) . '%';

		$searches = array();
		foreach ( $columns as $column ) {
			$searches[] = $wpdb->prepare( "$column LIKE %s", $like );
		}

		return '(' . implode( ' OR ', $searches ) . ')';
	}

	/**
	 * Parses and sanitizes 'orderby' keys passed to the network query.
	 *
	 * @since 4.6.0
	 *
	 * @global wpdb $wpdb WordPress database abstraction object.
	 *
	 * @param string $orderby Alias for the field to order by.
	 * @return string|false Value to used in the ORDER clause. False otherwise.
	 */
	protected function parse_orderby( $orderby ) {
		global $wpdb;

		$allowed_keys = array(
			'id',
			'domain',
			'path',
		);

		$parsed = false;
		if ( 'network__in' === $orderby ) {
			$network__in = implode( ',', array_map( 'absint', $this->query_vars['network__in'] ) );
			$parsed      = "FIELD( {$wpdb->site}.id, $network__in )";
		} elseif ( 'domain_length' === $orderby || 'path_length' === $orderby ) {
			$field  = substr( $orderby, 0, -7 );
			$parsed = "CHAR_LENGTH($wpdb->site.$field)";
		} elseif ( in_array( $orderby, $allowed_keys, true ) ) {
			$parsed = "$wpdb->site.$orderby";
		}

		return $parsed;
	}

	/**
	 * Parses an 'order' query variable and cast it to 'ASC' or 'DESC' as necessary.
	 *
	 * @since 4.6.0
	 *
	 * @param string $order The 'order' query variable.
	 * @return string The sanitized 'order' query variable.
	 */
	protected function parse_order( $order ) {
		if ( ! is_string( $order ) || empty( $order ) ) {
			return 'ASC';
		}

		if ( 'ASC' === strtoupper( $order ) ) {
			return 'ASC';
		} else {
			return 'DESC';
		}
	}
}

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As businesses increasingly rely on Software as a Service (SaaS) solutions for their operations, they are confronted with the inevitable reality of price increases. While these hikes can strain budgets and disrupt workflows, the emergence of AI-powered tools offers a glimmer of hope. In this article, we explore several innovative ways AI is helping organizations counter SaaS price increases.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/blockquote>\n

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How We Can Help You Save<\/h2>\n

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Several notable SaaS (Software as a Service) products have experienced significant price hikes over the years: Salesforce, GitHub, Zoom, and Zendesk for example.<\/span><\/p>\n

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    • We’ll build you your own and cut your software renewal fees.<\/li>\n
    • We analyze the software you use and how you use it<\/li>\n
    • We’ll write a proposal to cut out your vendors and replace it with software that you own.<\/li>\n
    • We can manage the hosting of your new software on public clouds such as Amazon AWS or Microsoft Azure.<\/li>\n
    • Based on typical clients, your replacement software will cost about 1-2 years of what you currently pay, but then cost only 10-20% to maintain than what you were paying before.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      Benefits and Advantages<\/h2>\n

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      Using AI to replace costly SaaS (Software as a Service) solutions can offer several benefits and advantages for organizations. Here are some compelling reasons to consider this approach:<\/p>\n

      Cost Savings:<\/strong> One of the primary reasons to replace costly SaaS solutions with AI-driven alternatives is cost savings. AI can automate tasks and processes that might require expensive software subscriptions. By building or integrating AI solutions, organizations can reduce their software expenses significantly.<\/p>\n

      Customization:<\/strong> AI solutions can be tailored to the specific needs of an organization. Unlike off-the-shelf SaaS products, which offer predefined features and functionalities, AI can be trained and customized to perform tasks and provide insights that align precisely with the organization’s requirements.<\/p>\n

      Scalability:<\/strong> AI solutions can often scale more efficiently than SaaS subscriptions. As your organization grows, you can expand your AI infrastructure without incurring linear increases in costs, unlike SaaS, where additional users or features can lead to higher subscription fees.<\/p>\n

      Data Security:<\/strong> AI solutions can be developed with a strong focus on data security and privacy. Organizations can have more control over their data, reducing the risk of data breaches or unauthorized access associated with third-party SaaS providers.<\/p>\n

      Integration:<\/strong> AI can seamlessly integrate with existing systems and workflows, allowing organizations to enhance their processes without disrupting their current operations. This integration can lead to increased efficiency and productivity.<\/p>\n

      Automation and Efficiency:<\/strong> AI can automate repetitive and time-consuming tasks, freeing up human resources for more strategic and value-added activities. This can result in increased efficiency and reduced labor costs.<\/p>\n

      Predictive Analytics:<\/strong> AI can provide valuable predictive insights that help organizations make data-driven decisions. This can be particularly beneficial in various industries, such as finance, healthcare, and marketing, where predictive analytics can lead to cost savings and revenue generation.<\/p>\n

      Long-term Cost Control:<\/strong> AI solutions typically involve upfront development costs but can provide long-term cost control as they do not rely on recurring subscription fees. This can be especially advantageous for organizations looking to manage their budgets over time.<\/p>\n

      Competitive Advantage:<\/strong> Organizations that successfully leverage AI to replace costly SaaS solutions may gain a competitive advantage. They can allocate resources strategically and invest in innovative solutions that differentiate them from competitors.<\/p>\n

      It’s important to note that while AI offers numerous advantages, its implementation can also come with challenges, including the need for skilled AI talent, data quality, and ethical considerations. The decision to replace SaaS with AI should be based on a thorough assessment of the organization’s specific needs, goals, and available resources.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      Smart SaaS Usage Optimization<\/h2>\n

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      AI-driven tools for monitoring SaaS application usage and recommending cost-efficient alternatives or unused features are transforming how organizations manage their software expenses:<\/p>\n

      Usage Tracking: These tools continuously monitor how employees use SaaS applications, collecting data on feature utilization, frequency, and user engagement.<\/p>\n

      Recommendation Engine: AI algorithms analyze usage data and compare it to available features and pricing plans. They identify cost-efficient alternatives within the same SaaS ecosystem or suggest unused features that can replace or supplement existing subscriptions.<\/p>\n

      Examples of Companies Saving Money:<\/strong><\/p>\n

      Company A<\/span>: After implementing an AI-driven usage monitoring tool, Company A identified that a significant portion of their team rarely used advanced features in their CRM software. By downgrading to a more cost-effective plan tailored to their actual needs, they reduced annual expenses by 30%.<\/p>\n

      Company B<\/span>: This tech startup found that their cloud storage expenses were steadily increasing. AI analysis revealed that many users were storing duplicate files unnecessarily. The AI tool recommended deduplication and a smarter file management strategy, resulting in a 25% reduction in storage costs.<\/p>\n

      Company C<\/span>: Company C was using multiple project management tools across different teams, leading to fragmented workflows and increased expenses. AI-driven analysis suggested consolidating to a single, more feature-rich solution that reduced subscription costs by 40%.<\/p>\n

      These examples highlight how AI-powered tools can help organizations make data-driven decisions, optimize their SaaS subscriptions, and achieve significant cost savings while maintaining or even improving productivity.<\/p>\n

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      SaaS Vendor Comparison and Alternatives<\/span><\/h2>\n

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      AI-driven platforms that compare SaaS vendors play a crucial role in simplifying the software selection process for businesses. These platforms utilize artificial intelligence and data analytics to:<\/p>\n

      Pricing Comparison<\/span>: They collect pricing data from various SaaS providers and present it in a unified, easy-to-compare format, allowing businesses to identify cost-effective options.<\/p>\n

      Feature Analysis<\/span>: AI algorithms analyze the features offered by different vendors and generate side-by-side comparisons, helping organizations find solutions that align with their specific needs.<\/p>\n

      User Reviews<\/span>: These platforms aggregate user reviews and sentiment analysis to provide insights into the user experience, reliability, and support quality of SaaS products.<\/p>\n

      Recommendations<\/span>: AI-driven platforms often offer tailored recommendations based on a company’s requirements and budget constraints, facilitating informed decision-making.<\/p>\n

      How Businesses Can Use These Platforms:<\/strong><\/p>\n

      Comprehensive Research<\/span>: Companies can use these platforms to gain a comprehensive understanding of the SaaS landscape, ensuring they make informed choices.<\/p>\n

      Cost-Efficiency<\/span>: By comparing pricing structures and available features, organizations can identify SaaS vendors that offer the best value for their investment.<\/p>\n

      User Satisfaction<\/span>: Analyzing user reviews and sentiment can help businesses gauge user satisfaction and potential issues with a particular vendor’s software.<\/p>\n

      Customization<\/span>: Businesses can tailor their search criteria to find SaaS solutions that precisely match their unique requirements, reducing the risk of overpaying for unnecessary features.<\/p>\n

      Time Savings<\/span>: These platforms streamline the research process, saving businesses valuable time that can be allocated to other critical tasks.<\/p>\n

      In a crowded SaaS market, AI-driven comparison platforms empower businesses to make well-informed decisions that align with their budget and needs, ultimately leading to more cost-effective and efficient software adoption.<\/p>\n

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      Case Studies<\/h2>\n

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      Case Study 1: Tech Innovators Inc.<\/strong><\/p>\n

      Background:<\/em> Tech Innovators Inc. is a medium-sized technology company that heavily relies on SaaS applications for various aspects of their operations. They’ve noticed recurring price hikes across multiple software tools, which posed a significant challenge to their budget management.<\/p>\n

      AI Solution Implementation:<\/em> Tech Innovators Inc. decided to implement an AI-driven cost prediction and optimization platform. The AI algorithms analyzed historical pricing data, detected patterns in price increases, and predicted potential future hikes for each SaaS product they used.<\/p>\n

      Results:<\/em><\/p>\n

      Proactive Budget Adjustments: With AI-generated price increase predictions, the company proactively adjusted their budgets to accommodate expected hikes.<\/p>\n

      Negotiation Success: Armed with data-backed insights, Tech Innovators Inc. engaged in more informed negotiations with their SaaS providers. They managed to secure better pricing terms and, in some cases, lock in current rates for an extended period.<\/p>\n

      Optimized Subscriptions: The AI platform identified several underutilized features in existing subscriptions and recommended downgrades to lower-tier plans, saving the company 15% on their SaaS expenses.<\/p>\n

      Case Study 2: Retail Plus Ltd.<\/strong><\/p>\n

      Background:<\/em> Retail Plus Ltd. is a national retail chain with numerous locations. They use various SaaS applications for inventory management, sales tracking, and customer engagement. Rising SaaS costs were impacting their profitability.<\/p>\n

      AI Solution Implementation:<\/em> Retail Plus Ltd. adopted an AI-powered SaaS optimization tool that continuously monitored usage patterns across their stores. It recommended cost-effective alternatives and identified unused features within their existing subscriptions.<\/p>\n

      Results:<\/em><\/p>\n

      Cost Reduction: The AI tool helped Retail Plus Ltd. identify duplicate SaaS subscriptions across different store locations. By consolidating these subscriptions and renegotiating with providers, they reduced SaaS expenses by 20%.<\/p>\n

      Improved Efficiency: By pinpointing underutilized features, the company optimized their workflows, enhancing operational efficiency and customer service.<\/p>\n

      Vendor Negotiations: With data-driven insights into their SaaS usage, Retail Plus Ltd. entered into more productive negotiations with their vendors, securing discounts and improved support packages.<\/p>\n

      These case studies showcase how AI-powered solutions can empower companies to proactively manage SaaS costs, negotiate effectively, and optimize their software subscriptions, ultimately resulting in significant cost savings and improved operational efficiency.<\/p>\n

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      Final Thoughts<\/h2>\n

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      In the ever-evolving landscape of Software as a Service (SaaS), where innovation and convenience often come with a price, AI-powered solutions are emerging as a formidable shield against the challenges of SaaS price hikes. As we’ve explored in this article, AI’s ability to analyze historical pricing data, optimize SaaS usage, and forecast future costs is transforming the way businesses approach software subscriptions.<\/p>\n

      No longer do organizations need to navigate the murky waters of SaaS pricing changes blindly. With AI-driven predictive models, companies can anticipate and plan for potential price increases, ensuring that their budgets remain on track and their financial stability intact. This proactive approach is not just a means of cost management; it’s a strategic advantage in a world where agility and adaptability are paramount.<\/p>\n

      AI also plays a pivotal role in optimizing SaaS usage. By monitoring application usage and recommending cost-efficient alternatives or unused features, businesses can trim unnecessary expenses while maintaining productivity. These AI-driven insights are more than just cost savings; they’re a pathway to efficiency and competitiveness.<\/p>\n

      Moreover, AI isn’t just a financial tool; it’s a negotiation partner. Armed with AI-driven insights, businesses can engage in informed discussions with SaaS providers, leveraging data-backed arguments to secure more favorable contracts. Negotiating from a position of strength is the cornerstone of smart cost management.<\/p>\n

      As we’ve seen from real-world examples, companies are reaping the rewards of AI-powered SaaS cost optimization. They are reducing expenses, reallocating resources, and making strategic decisions that position them for long-term success. In the face of unpredictable pricing landscapes, AI is the ally that empowers organizations to take control of their software costs.<\/p>\n

      In conclusion, the era of SaaS price hikes need not be a source of anxiety or frustration. Instead, it’s an opportunity for businesses to embrace AI-powered solutions that provide clarity, control, and cost-effectiveness. As AI continues to evolve, its role in shielding businesses against SaaS price hikes is destined to become even more indispensable, enabling organizations to thrive in a digital world where innovation meets fiscal responsibility.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      As businesses increasingly rely on Software as a Service (SaaS) solutions for their operations, they are confronted with the inevitable reality of price increases. While these hikes can strain budgets and disrupt workflows, the emergence of AI-powered tools offers a glimmer of hope.<\/p>\n","protected":false},"author":3,"featured_media":7783,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[2316,567,59,122],"tags":[51,2421,126,123],"class_list":["post-7779","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-agents","category-artificial-intelligence","category-custom-software-development","category-saas-replacement","tag-ai","tag-ai-solutions","tag-saas","tag-saas-replacement"],"yoast_head":"